Overview

Dataset statistics

Number of variables39
Number of observations25 525
Missing cells72 118
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 MiB
Average record size in memory284.0 B

Variable types

Categorical25
Numeric9
Boolean5

Alerts

Adult has constant value "False" Constant
date_time has a high cardinality: 11248 distinct values High cardinality
Film has a high cardinality: 1075 distinct values High cardinality
FullTitle has a high cardinality: 1009 distinct values High cardinality
Release has a high cardinality: 665 distinct values High cardinality
Genre has a high cardinality: 335 distinct values High cardinality
Overview has a high cardinality: 957 distinct values High cardinality
Humidité has a high cardinality: 55 distinct values High cardinality
Visibilité has a high cardinality: 54 distinct values High cardinality
Couverture nuageuse has a high cardinality: 101 distinct values High cardinality
Heure du lever du soleil has a high cardinality: 210 distinct values High cardinality
Heure du coucher du soleil has a high cardinality: 269 distinct values High cardinality
Durée du jour has a high cardinality: 372 distinct values High cardinality
Payants is highly correlated with Places libres and 2 other fieldsHigh correlation
Taux remplissage is highly correlated with Payants and 2 other fieldsHigh correlation
Popularity is highly correlated with Vote_countHigh correlation
Vote_average is highly correlated with Vote_countHigh correlation
Vote_count is highly correlated with Version and 1 other fieldsHigh correlation
vacances_zone_a is highly correlated with vacances_zone_b and 2 other fieldsHigh correlation
vacances_zone_b is highly correlated with vacances_zone_a and 2 other fieldsHigh correlation
vacances_zone_c is highly correlated with vacances_zone_a and 2 other fieldsHigh correlation
Nombre entrees is highly correlated with Payants and 2 other fieldsHigh correlation
Visibilité is highly correlated with Température maximale and 10 other fieldsHigh correlation
Adult is highly correlated with Visibilité and 18 other fieldsHigh correlation
Salle is highly correlated with Places libresHigh correlation
L'avis de historique-meteo.net is highly correlated with Température maximale and 9 other fieldsHigh correlation
Version is highly correlated with Language and 1 other fieldsHigh correlation
Relief is highly correlated with AdultHigh correlation
Pression is highly correlated with Température maximale and 10 other fieldsHigh correlation
Température du vent is highly correlated with Température maximale and 10 other fieldsHigh correlation
Point de rosée is highly correlated with Température maximale and 10 other fieldsHigh correlation
Température maximale is highly correlated with Température minimale and 10 other fieldsHigh correlation
Language is highly correlated with VersionHigh correlation
Température minimale is highly correlated with Température maximale and 10 other fieldsHigh correlation
Vitesse du vent is highly correlated with Température maximale and 8 other fieldsHigh correlation
Précipitations is highly correlated with Température maximale and 10 other fieldsHigh correlation
ferie is highly correlated with AdultHigh correlation
Humidité is highly correlated with Température maximale and 10 other fieldsHigh correlation
nom_vacances is highly correlated with Température maximale and 13 other fieldsHigh correlation
Places libres is highly correlated with Salle and 3 other fieldsHigh correlation
Indice de chaleur is highly correlated with Température maximale and 9 other fieldsHigh correlation
Payants has 2339 (9.2%) missing values Missing
Gratuits has 22055 (86.4%) missing values Missing
Taux remplissage has 2265 (8.9%) missing values Missing
Release has 301 (1.2%) missing values Missing
Genre has 685 (2.7%) missing values Missing
Vote_average has 1501 (5.9%) missing values Missing
Vote_count has 1501 (5.9%) missing values Missing
Overview has 1145 (4.5%) missing values Missing
Température maximale has 1338 (5.2%) missing values Missing
Température minimale has 1338 (5.2%) missing values Missing
Vitesse du vent has 1338 (5.2%) missing values Missing
Température du vent has 1338 (5.2%) missing values Missing
Précipitations has 6460 (25.3%) missing values Missing
Humidité has 1338 (5.2%) missing values Missing
Visibilité has 1338 (5.2%) missing values Missing
Couverture nuageuse has 1338 (5.2%) missing values Missing
Indice de chaleur has 1338 (5.2%) missing values Missing
Point de rosée has 1823 (7.1%) missing values Missing
Pression has 1338 (5.2%) missing values Missing
Heure du lever du soleil has 1338 (5.2%) missing values Missing
Heure du coucher du soleil has 1338 (5.2%) missing values Missing
Durée du jour has 1338 (5.2%) missing values Missing
L'avis de historique-meteo.net has 1338 (5.2%) missing values Missing
nom_vacances has 13851 (54.3%) missing values Missing
Nombre entrees has 2268 (8.9%) zeros Zeros

Reproduction

Analysis started2022-10-13 07:31:53.116639
Analysis finished2022-10-13 07:32:48.112433
Duration55 seconds
Software versionpandas-profiling v3.3.0
Download configurationconfig.json

Variables

date_time
Categorical

HIGH CARDINALITY

Distinct11248
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Memory size199.5 KiB
2021-12-20 13:30:00
 
7
2022-02-26 18:30:00
 
7
2022-02-25 21:00:00
 
7
2021-12-26 21:00:00
 
6
2019-08-27 13:30:00
 
6
Other values (11243)
25492 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters484 975
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5229 ?
Unique (%)20.5%

Sample

1st row2018-11-27 09:45:00
2nd row2018-11-27 10:55:00
3rd row2018-11-27 14:00:00
4th row2018-11-27 20:30:00
5th row2018-11-27 20:30:00

Common Values

ValueCountFrequency (%)
2021-12-20 13:30:007
 
< 0.1%
2022-02-26 18:30:007
 
< 0.1%
2022-02-25 21:00:007
 
< 0.1%
2021-12-26 21:00:006
 
< 0.1%
2019-08-27 13:30:006
 
< 0.1%
2022-06-02 15:30:006
 
< 0.1%
2019-04-01 13:50:006
 
< 0.1%
2019-08-27 21:00:006
 
< 0.1%
2019-08-28 13:30:006
 
< 0.1%
2022-03-04 15:30:006
 
< 0.1%
Other values (11238)25462
99.8%

Length

2022-10-13T09:32:48.357561image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
21:00:003097
 
6.1%
13:30:002709
 
5.3%
18:30:001655
 
3.2%
16:00:001611
 
3.2%
11:00:001592
 
3.1%
13:50:001455
 
2.9%
20:30:001170
 
2.3%
18:20:00973
 
1.9%
18:00:00949
 
1.9%
15:30:00685
 
1.3%
Other values (1184)35154
68.9%

Most occurring characters

ValueCountFrequency (%)
0146158
30.1%
270134
14.5%
163850
13.2%
-51050
 
10.5%
:51050
 
10.5%
25525
 
5.3%
317373
 
3.6%
914326
 
3.0%
512341
 
2.5%
810839
 
2.2%
Other values (3)22329
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number357350
73.7%
Dash Punctuation51050
 
10.5%
Other Punctuation51050
 
10.5%
Space Separator25525
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0146158
40.9%
270134
19.6%
163850
17.9%
317373
 
4.9%
914326
 
4.0%
512341
 
3.5%
810839
 
3.0%
68090
 
2.3%
48083
 
2.3%
76156
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
-51050
100.0%
Other Punctuation
ValueCountFrequency (%)
:51050
100.0%
Space Separator
ValueCountFrequency (%)
25525
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common484975
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0146158
30.1%
270134
14.5%
163850
13.2%
-51050
 
10.5%
:51050
 
10.5%
25525
 
5.3%
317373
 
3.6%
914326
 
3.0%
512341
 
2.5%
810839
 
2.2%
Other values (3)22329
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII484975
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0146158
30.1%
270134
14.5%
163850
13.2%
-51050
 
10.5%
:51050
 
10.5%
25525
 
5.3%
317373
 
3.6%
914326
 
3.0%
512341
 
2.5%
810839
 
2.2%
Other values (3)22329
 
4.6%

Salle
Categorical

HIGH CORRELATION

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size199.5 KiB
SALLE 1
4324 
SALLE 5
4285 
SALLE 4
4261 
SALLE 3
4259 
SALLE 2
4248 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters178 675
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSALLE 6
2nd rowSALLE 2
3rd rowSALLE 2
4th rowSALLE 1
5th rowSALLE 2

Common Values

ValueCountFrequency (%)
SALLE 14324
16.9%
SALLE 54285
16.8%
SALLE 44261
16.7%
SALLE 34259
16.7%
SALLE 24248
16.6%
SALLE 64148
16.3%

Length

2022-10-13T09:32:48.602684image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-13T09:32:48.964695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
salle25525
50.0%
14324
 
8.5%
54285
 
8.4%
44261
 
8.3%
34259
 
8.3%
24248
 
8.3%
64148
 
8.1%

Most occurring characters

ValueCountFrequency (%)
L51050
28.6%
S25525
14.3%
A25525
14.3%
E25525
14.3%
25525
14.3%
14324
 
2.4%
54285
 
2.4%
44261
 
2.4%
34259
 
2.4%
24248
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter127625
71.4%
Space Separator25525
 
14.3%
Decimal Number25525
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
14324
16.9%
54285
16.8%
44261
16.7%
34259
16.7%
24248
16.6%
64148
16.3%
Uppercase Letter
ValueCountFrequency (%)
L51050
40.0%
S25525
20.0%
A25525
20.0%
E25525
20.0%
Space Separator
ValueCountFrequency (%)
25525
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin127625
71.4%
Common51050
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
25525
50.0%
14324
 
8.5%
54285
 
8.4%
44261
 
8.3%
34259
 
8.3%
24248
 
8.3%
64148
 
8.1%
Latin
ValueCountFrequency (%)
L51050
40.0%
S25525
20.0%
A25525
20.0%
E25525
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII178675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L51050
28.6%
S25525
14.3%
A25525
14.3%
E25525
14.3%
25525
14.3%
14324
 
2.4%
54285
 
2.4%
44261
 
2.4%
34259
 
2.4%
24248
 
2.4%

Film
Categorical

HIGH CARDINALITY

Distinct1075
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size199.5 KiB
Le Roi Lion
 
210
La Reine Des Neiges 2
 
174
Jumanji: Next Level
 
147
Top Gun: Maverick
 
143
Toy Story 4
 
142
Other values (1070)
24709 

Length

Max length50
Median length39
Mean length17.55357493
Min length2

Characters and Unicode

Total characters448 055
Distinct characters100
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)0.7%

Sample

1st rowL'île De Black Mór
2nd rowDiamant Noir
3rd rowSobibor, 14 Octobre 1943, 16 Heures
4th rowCold War
5th rowBohemian Rhapsody

Common Values

ValueCountFrequency (%)
Le Roi Lion210
 
0.8%
La Reine Des Neiges 2174
 
0.7%
Jumanji: Next Level147
 
0.6%
Top Gun: Maverick143
 
0.6%
Toy Story 4142
 
0.6%
Qu'est-ce Qu'on A Encore Fait Au Bon Dieu ?132
 
0.5%
Star Wars: L'ascension De Skywalker132
 
0.5%
Comme Des Bêtes 2126
 
0.5%
Spider-man: Far From Home122
 
0.5%
Encanto, La Fantastique Famille Madrigal118
 
0.5%
Other values (1065)24079
94.3%

Length

2022-10-13T09:32:49.328707image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
le3495
 
4.2%
3308
 
4.0%
la2994
 
3.6%
les2556
 
3.1%
de2214
 
2.7%
21293
 
1.6%
et1209
 
1.5%
des1148
 
1.4%
du1015
 
1.2%
en766
 
0.9%
Other values (1779)62972
75.9%

Most occurring characters

ValueCountFrequency (%)
57445
 
12.8%
e49352
 
11.0%
a27110
 
6.1%
i24558
 
5.5%
n22990
 
5.1%
o22571
 
5.0%
r21748
 
4.9%
s21507
 
4.8%
t18020
 
4.0%
u16647
 
3.7%
Other values (90)166107
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter298594
66.6%
Uppercase Letter76739
 
17.1%
Space Separator57445
 
12.8%
Other Punctuation8884
 
2.0%
Decimal Number3927
 
0.9%
Dash Punctuation2130
 
0.5%
Final Punctuation193
 
< 0.1%
Open Punctuation73
 
< 0.1%
Close Punctuation67
 
< 0.1%
Other Symbol3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e49352
16.5%
a27110
9.1%
i24558
8.2%
n22990
 
7.7%
o22571
 
7.6%
r21748
 
7.3%
s21507
 
7.2%
t18020
 
6.0%
u16647
 
5.6%
l14952
 
5.0%
Other values (31)59139
19.8%
Uppercase Letter
ValueCountFrequency (%)
L12423
16.2%
D7879
 
10.3%
M6035
 
7.9%
C4652
 
6.1%
S4580
 
6.0%
A4322
 
5.6%
P4190
 
5.5%
F4109
 
5.4%
E3558
 
4.6%
T3393
 
4.4%
Other values (21)21598
28.1%
Other Punctuation
ValueCountFrequency (%)
'3251
36.6%
:2771
31.2%
!807
 
9.1%
,645
 
7.3%
.485
 
5.5%
?468
 
5.3%
&279
 
3.1%
98
 
1.1%
#45
 
0.5%
%29
 
0.3%
Decimal Number
ValueCountFrequency (%)
21530
39.0%
1605
 
15.4%
0432
 
11.0%
3366
 
9.3%
4298
 
7.6%
9180
 
4.6%
7159
 
4.0%
5135
 
3.4%
6126
 
3.2%
896
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
-1971
92.5%
159
 
7.5%
Space Separator
ValueCountFrequency (%)
57445
100.0%
Final Punctuation
ValueCountFrequency (%)
193
100.0%
Open Punctuation
ValueCountFrequency (%)
(73
100.0%
Close Punctuation
ValueCountFrequency (%)
)67
100.0%
Other Symbol
ValueCountFrequency (%)
°3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin375333
83.8%
Common72722
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e49352
 
13.1%
a27110
 
7.2%
i24558
 
6.5%
n22990
 
6.1%
o22571
 
6.0%
r21748
 
5.8%
s21507
 
5.7%
t18020
 
4.8%
u16647
 
4.4%
l14952
 
4.0%
Other values (62)135878
36.2%
Common
ValueCountFrequency (%)
57445
79.0%
'3251
 
4.5%
:2771
 
3.8%
-1971
 
2.7%
21530
 
2.1%
!807
 
1.1%
,645
 
0.9%
1605
 
0.8%
.485
 
0.7%
?468
 
0.6%
Other values (18)2744
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII440703
98.4%
None6902
 
1.5%
Punctuation450
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57445
 
13.0%
e49352
 
11.2%
a27110
 
6.2%
i24558
 
5.6%
n22990
 
5.2%
o22571
 
5.1%
r21748
 
4.9%
s21507
 
4.9%
t18020
 
4.1%
u16647
 
3.8%
Other values (66)158755
36.0%
None
ValueCountFrequency (%)
é3844
55.7%
è1308
 
19.0%
ê478
 
6.9%
à447
 
6.5%
â177
 
2.6%
ï111
 
1.6%
ù88
 
1.3%
À79
 
1.1%
ô68
 
1.0%
î64
 
0.9%
Other values (11)238
 
3.4%
Punctuation
ValueCountFrequency (%)
193
42.9%
159
35.3%
98
21.8%

Version
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size199.5 KiB
FR
13069 
VF
10670 
VO
1786 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters51 050
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFR
2nd rowFR
3rd rowFR
4th rowVO
5th rowVF

Common Values

ValueCountFrequency (%)
FR13069
51.2%
VF10670
41.8%
VO1786
 
7.0%

Length

2022-10-13T09:32:49.605719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-13T09:32:49.781724image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
fr13069
51.2%
vf10670
41.8%
vo1786
 
7.0%

Most occurring characters

ValueCountFrequency (%)
F23739
46.5%
R13069
25.6%
V12456
24.4%
O1786
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter51050
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F23739
46.5%
R13069
25.6%
V12456
24.4%
O1786
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin51050
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F23739
46.5%
R13069
25.6%
V12456
24.4%
O1786
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII51050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F23739
46.5%
R13069
25.6%
V12456
24.4%
O1786
 
3.5%

Relief
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size199.5 KiB
2D
25444 
3D
 
73
IND
 
8

Length

Max length3
Median length2
Mean length2.000313418
Min length2

Characters and Unicode

Total characters51 058
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2D
2nd row2D
3rd row2D
4th row2D
5th row2D

Common Values

ValueCountFrequency (%)
2D25444
99.7%
3D73
 
0.3%
IND8
 
< 0.1%

Length

2022-10-13T09:32:49.943740image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-13T09:32:50.172743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2d25444
99.7%
3d73
 
0.3%
ind8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
D25525
50.0%
225444
49.8%
373
 
0.1%
I8
 
< 0.1%
N8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter25541
50.0%
Decimal Number25517
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D25525
99.9%
I8
 
< 0.1%
N8
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
225444
99.7%
373
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin25541
50.0%
Common25517
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
D25525
99.9%
I8
 
< 0.1%
N8
 
< 0.1%
Common
ValueCountFrequency (%)
225444
99.7%
373
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII51058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D25525
50.0%
225444
49.8%
373
 
0.1%
I8
 
< 0.1%
N8
 
< 0.1%

Payants
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct242
Distinct (%)1.0%
Missing2339
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean20.98296386
Minimum1
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:50.451754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median11
Q325
95-th percentile74
Maximum288
Range287
Interquartile range (IQR)20

Descriptive statistics

Standard deviation28.16248204
Coefficient of variation (CV)1.342159393
Kurtosis19.67711074
Mean20.98296386
Median Absolute Deviation (MAD)8
Skewness3.608122371
Sum486511
Variance793.1253945
MonotonicityNot monotonic
2022-10-13T09:32:50.699285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21764
 
6.9%
41428
 
5.6%
31236
 
4.8%
51163
 
4.6%
61140
 
4.5%
8957
 
3.7%
7953
 
3.7%
1877
 
3.4%
9833
 
3.3%
10763
 
3.0%
Other values (232)12072
47.3%
(Missing)2339
 
9.2%
ValueCountFrequency (%)
1877
3.4%
21764
6.9%
31236
4.8%
41428
5.6%
51163
4.6%
61140
4.5%
7953
3.7%
8957
3.7%
9833
3.3%
10763
3.0%
ValueCountFrequency (%)
2881
 
< 0.1%
2873
< 0.1%
2862
 
< 0.1%
2855
< 0.1%
2843
< 0.1%
2831
 
< 0.1%
2821
 
< 0.1%
2814
< 0.1%
2801
 
< 0.1%
2781
 
< 0.1%

Gratuits
Real number (ℝ≥0)

MISSING

Distinct24
Distinct (%)0.7%
Missing22055
Missing (%)86.4%
Infinite0
Infinite (%)0.0%
Mean2.771181556
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:50.883283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile8
Maximum78
Range77
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.005823029
Coefficient of variation (CV)1.084671996
Kurtosis130.774908
Mean2.771181556
Median Absolute Deviation (MAD)1
Skewness7.351298183
Sum9616
Variance9.034972083
MonotonicityNot monotonic
2022-10-13T09:32:51.052583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11215
 
4.8%
21150
 
4.5%
3366
 
1.4%
4240
 
0.9%
5139
 
0.5%
692
 
0.4%
772
 
0.3%
847
 
0.2%
1035
 
0.1%
931
 
0.1%
Other values (14)83
 
0.3%
(Missing)22055
86.4%
ValueCountFrequency (%)
11215
4.8%
21150
4.5%
3366
 
1.4%
4240
 
0.9%
5139
 
0.5%
692
 
0.4%
772
 
0.3%
847
 
0.2%
931
 
0.1%
1035
 
0.1%
ValueCountFrequency (%)
781
 
< 0.1%
451
 
< 0.1%
242
 
< 0.1%
232
 
< 0.1%
222
 
< 0.1%
202
 
< 0.1%
182
 
< 0.1%
176
< 0.1%
164
 
< 0.1%
1512
< 0.1%

Places libres
Real number (ℝ≥0)

HIGH CORRELATION

Distinct288
Distinct (%)1.1%
Missing30
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean133.9364974
Minimum1
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:51.236826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile62
Q188
median110
Q3175
95-th percentile280
Maximum288
Range287
Interquartile range (IQR)87

Descriptive statistics

Standard deviation66.25595387
Coefficient of variation (CV)0.4946818469
Kurtosis0.03883319662
Mean133.9364974
Median Absolute Deviation (MAD)29
Skewness0.9866758175
Sum3414711
Variance4389.851423
MonotonicityNot monotonic
2022-10-13T09:32:51.390095image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
931029
 
4.0%
91790
 
3.1%
89664
 
2.6%
90580
 
2.3%
88523
 
2.0%
92493
 
1.9%
87473
 
1.9%
114434
 
1.7%
86419
 
1.6%
85405
 
1.6%
Other values (278)19685
77.1%
ValueCountFrequency (%)
118
0.1%
210
< 0.1%
38
< 0.1%
46
 
< 0.1%
58
< 0.1%
64
 
< 0.1%
711
< 0.1%
83
 
< 0.1%
93
 
< 0.1%
105
 
< 0.1%
ValueCountFrequency (%)
288259
1.0%
28791
 
0.4%
286193
0.8%
285113
0.4%
284176
0.7%
283126
0.5%
282131
0.5%
281131
0.5%
280112
0.4%
27990
 
0.4%

Taux remplissage
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct529
Distinct (%)2.3%
Missing2265
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean14.12412683
Minimum0.35
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:51.562789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0.35
5-th percentile1.08
Q13.51
median8.33
Q318.06
95-th percentile48.61
Maximum100
Range99.65
Interquartile range (IQR)14.55

Descriptive statistics

Standard deviation16.24760314
Coefficient of variation (CV)1.1503439
Kurtosis6.291481988
Mean14.12412683
Median Absolute Deviation (MAD)5.7
Skewness2.318298183
Sum328527.19
Variance263.9846079
MonotonicityNot monotonic
2022-10-13T09:32:51.735798image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.15719
 
2.8%
4.3607
 
2.4%
3.23526
 
2.1%
2.08503
 
2.0%
5.38480
 
1.9%
4.17458
 
1.8%
1.39439
 
1.7%
1.08425
 
1.7%
6.45424
 
1.7%
1.04369
 
1.4%
Other values (519)18310
71.7%
(Missing)2265
 
8.9%
ValueCountFrequency (%)
0.3591
 
0.4%
0.52118
 
0.5%
0.69312
1.2%
0.88132
 
0.5%
1.04369
1.4%
1.08425
1.7%
1.39439
1.7%
1.56166
 
0.7%
1.74126
 
0.5%
1.75311
1.2%
ValueCountFrequency (%)
10030
0.1%
99.655
 
< 0.1%
99.317
 
< 0.1%
99.121
 
< 0.1%
98.965
 
< 0.1%
98.927
 
< 0.1%
98.614
 
< 0.1%
98.261
 
< 0.1%
98.251
 
< 0.1%
97.853
 
< 0.1%

FullTitle
Categorical

HIGH CARDINALITY

Distinct1009
Distinct (%)4.0%
Missing192
Missing (%)0.8%
Memory size199.5 KiB
Explorez le Festival du Roi Lion & de la Jungle
 
210
Sonic the Hedgehog 3
 
192
Frozen II
 
174
The Addams Family 2
 
166
Fast X
 
152
Other values (1004)
24439 

Length

Max length68
Median length41
Mean length17.50487506
Min length3

Characters and Unicode

Total characters443 451
Distinct characters338
Distinct categories14 ?
Distinct scripts13 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)0.6%

Sample

1st rowL'île de Black Mór
2nd rowDiamant noir
3rd rowSobibor, 14 Octobre 1943, 16 Heures
4th rowCold War
5th rowBohemian Rhapsody

Common Values

ValueCountFrequency (%)
Explorez le Festival du Roi Lion & de la Jungle210
 
0.8%
Sonic the Hedgehog 3192
 
0.8%
Frozen II174
 
0.7%
The Addams Family 2166
 
0.7%
Fast X152
 
0.6%
Jumanji: The Next Level147
 
0.6%
Top Gun: Maverick143
 
0.6%
Toy Story 4142
 
0.6%
Qu'est-ce qu'on a encore fait au Bon Dieu ?132
 
0.5%
Star Wars: The Rise of Skywalker132
 
0.5%
Other values (999)23743
93.0%
(Missing)192
 
0.8%

Length

2022-10-13T09:32:51.930368image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the4005
 
5.0%
la2089
 
2.6%
1823
 
2.3%
de1809
 
2.2%
le1769
 
2.2%
les1612
 
2.0%
of1393
 
1.7%
du747
 
0.9%
en699
 
0.9%
et680
 
0.8%
Other values (1808)64156
79.4%

Most occurring characters

ValueCountFrequency (%)
55441
 
12.5%
e49932
 
11.3%
a26787
 
6.0%
i23703
 
5.3%
o23640
 
5.3%
n23341
 
5.3%
r22083
 
5.0%
s20669
 
4.7%
t19950
 
4.5%
l16926
 
3.8%
Other values (328)160979
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter318049
71.7%
Space Separator55449
 
12.5%
Uppercase Letter53392
 
12.0%
Other Punctuation7529
 
1.7%
Other Letter3806
 
0.9%
Decimal Number2654
 
0.6%
Dash Punctuation1734
 
0.4%
Modifier Letter440
 
0.1%
Final Punctuation113
 
< 0.1%
Close Punctuation102
 
< 0.1%
Other values (4)183
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
195
 
5.1%
138
 
3.6%
120
 
3.2%
112
 
2.9%
99
 
2.6%
87
 
2.3%
83
 
2.2%
71
 
1.9%
64
 
1.7%
64
 
1.7%
Other values (179)2773
72.9%
Lowercase Letter
ValueCountFrequency (%)
e49932
15.7%
a26787
 
8.4%
i23703
 
7.5%
o23640
 
7.4%
n23341
 
7.3%
r22083
 
6.9%
s20669
 
6.5%
t19950
 
6.3%
l16926
 
5.3%
u14710
 
4.6%
Other values (61)76308
24.0%
Uppercase Letter
ValueCountFrequency (%)
L6060
 
11.4%
T5304
 
9.9%
M4106
 
7.7%
D3498
 
6.6%
S3453
 
6.5%
A3445
 
6.5%
C3089
 
5.8%
P2902
 
5.4%
B2751
 
5.2%
F2176
 
4.1%
Other values (26)16608
31.1%
Other Punctuation
ValueCountFrequency (%)
:2668
35.4%
'2439
32.4%
!773
 
10.3%
?442
 
5.9%
,441
 
5.9%
&300
 
4.0%
.236
 
3.1%
118
 
1.6%
45
 
0.6%
%29
 
0.4%
Other values (7)38
 
0.5%
Decimal Number
ValueCountFrequency (%)
2610
23.0%
1518
19.5%
3387
14.6%
0331
12.5%
4297
11.2%
7153
 
5.8%
5129
 
4.9%
9119
 
4.5%
896
 
3.6%
614
 
0.5%
Space Separator
ValueCountFrequency (%)
55441
> 99.9%
 8
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-1710
98.6%
24
 
1.4%
Close Punctuation
ValueCountFrequency (%)
)66
64.7%
36
35.3%
Open Punctuation
ValueCountFrequency (%)
(66
64.7%
36
35.3%
Nonspacing Mark
ValueCountFrequency (%)
36
81.8%
8
 
18.2%
Spacing Mark
ValueCountFrequency (%)
ി18
66.7%
9
33.3%
Modifier Letter
ValueCountFrequency (%)
440
100.0%
Final Punctuation
ValueCountFrequency (%)
113
100.0%
Format
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin371335
83.7%
Common68107
 
15.4%
Katakana1626
 
0.4%
Han1110
 
0.3%
Arabic413
 
0.1%
Hiragana326
 
0.1%
Hangul142
 
< 0.1%
Malayalam135
 
< 0.1%
Greek88
 
< 0.1%
Hebrew77
 
< 0.1%
Other values (3)92
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e49932
 
13.4%
a26787
 
7.2%
i23703
 
6.4%
o23640
 
6.4%
n23341
 
6.3%
r22083
 
5.9%
s20669
 
5.6%
t19950
 
5.4%
l16926
 
4.6%
u14710
 
4.0%
Other values (75)129594
34.9%
Han
ValueCountFrequency (%)
62
 
5.6%
62
 
5.6%
62
 
5.6%
48
 
4.3%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
Other values (65)660
59.5%
Common
ValueCountFrequency (%)
55441
81.4%
:2668
 
3.9%
'2439
 
3.6%
-1710
 
2.5%
!773
 
1.1%
2610
 
0.9%
1518
 
0.8%
?442
 
0.6%
,441
 
0.6%
440
 
0.6%
Other values (26)2625
 
3.9%
Katakana
ValueCountFrequency (%)
195
 
12.0%
120
 
7.4%
112
 
6.9%
99
 
6.1%
87
 
5.4%
83
 
5.1%
71
 
4.4%
64
 
3.9%
64
 
3.9%
56
 
3.4%
Other values (26)675
41.5%
Arabic
ValueCountFrequency (%)
ی49
11.9%
ش41
9.9%
و40
9.7%
م40
9.7%
ن40
9.7%
ا31
7.5%
ر30
 
7.3%
د29
 
7.0%
ت24
 
5.8%
ب12
 
2.9%
Other values (14)77
18.6%
Hiragana
ValueCountFrequency (%)
138
42.3%
20
 
6.1%
18
 
5.5%
16
 
4.9%
13
 
4.0%
12
 
3.7%
12
 
3.7%
12
 
3.7%
9
 
2.8%
9
 
2.8%
Other values (11)67
20.6%
Hangul
ValueCountFrequency (%)
12
 
8.5%
12
 
8.5%
12
 
8.5%
11
 
7.7%
11
 
7.7%
11
 
7.7%
9
 
6.3%
9
 
6.3%
9
 
6.3%
9
 
6.3%
Other values (5)37
26.1%
Greek
ValueCountFrequency (%)
Η8
9.1%
Δ8
9.1%
ο8
9.1%
υ8
9.1%
λ8
9.1%
ε8
9.1%
ι8
9.1%
Τ8
9.1%
η8
9.1%
ς8
9.1%
Cyrillic
ValueCountFrequency (%)
т3
16.7%
и3
16.7%
о2
11.1%
с2
11.1%
р2
11.1%
И1
 
5.6%
д1
 
5.6%
м1
 
5.6%
в1
 
5.6%
а1
 
5.6%
Malayalam
ValueCountFrequency (%)
36
26.7%
18
13.3%
18
13.3%
ി18
13.3%
9
 
6.7%
9
 
6.7%
9
 
6.7%
9
 
6.7%
9
 
6.7%
Hebrew
ValueCountFrequency (%)
ל14
18.2%
א14
18.2%
ב14
18.2%
ה7
9.1%
י7
9.1%
ע7
9.1%
ש7
9.1%
ת7
9.1%
Tibetan
ValueCountFrequency (%)
16
25.0%
16
25.0%
8
12.5%
8
12.5%
8
12.5%
8
12.5%
Inherited
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII433624
97.8%
None5165
 
1.2%
Katakana2111
 
0.5%
CJK1110
 
0.3%
Arabic414
 
0.1%
Hiragana326
 
0.1%
Punctuation265
 
0.1%
Hangul142
 
< 0.1%
Malayalam135
 
< 0.1%
Hebrew77
 
< 0.1%
Other values (2)82
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55441
 
12.8%
e49932
 
11.5%
a26787
 
6.2%
i23703
 
5.5%
o23640
 
5.5%
n23341
 
5.4%
r22083
 
5.1%
s20669
 
4.8%
t19950
 
4.6%
l16926
 
3.9%
Other values (67)151152
34.9%
None
ValueCountFrequency (%)
é2542
49.2%
è716
 
13.9%
ê318
 
6.2%
à238
 
4.6%
É190
 
3.7%
â118
 
2.3%
î95
 
1.8%
À89
 
1.7%
ï85
 
1.6%
ä75
 
1.5%
Other values (39)699
 
13.5%
Katakana
ValueCountFrequency (%)
440
20.8%
195
 
9.2%
120
 
5.7%
112
 
5.3%
99
 
4.7%
87
 
4.1%
83
 
3.9%
71
 
3.4%
64
 
3.0%
64
 
3.0%
Other values (28)776
36.8%
Hiragana
ValueCountFrequency (%)
138
42.3%
20
 
6.1%
18
 
5.5%
16
 
4.9%
13
 
4.0%
12
 
3.7%
12
 
3.7%
12
 
3.7%
9
 
2.8%
9
 
2.8%
Other values (11)67
20.6%
Punctuation
ValueCountFrequency (%)
118
44.5%
113
42.6%
24
 
9.1%
10
 
3.8%
CJK
ValueCountFrequency (%)
62
 
5.6%
62
 
5.6%
62
 
5.6%
48
 
4.3%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
36
 
3.2%
Other values (65)660
59.5%
Arabic
ValueCountFrequency (%)
ی49
11.8%
ش41
9.9%
و40
9.7%
م40
9.7%
ن40
9.7%
ا31
 
7.5%
ر30
 
7.2%
د29
 
7.0%
ت24
 
5.8%
ب12
 
2.9%
Other values (15)78
18.8%
Malayalam
ValueCountFrequency (%)
36
26.7%
18
13.3%
18
13.3%
ി18
13.3%
9
 
6.7%
9
 
6.7%
9
 
6.7%
9
 
6.7%
9
 
6.7%
Tibetan
ValueCountFrequency (%)
16
25.0%
16
25.0%
8
12.5%
8
12.5%
8
12.5%
8
12.5%
Hebrew
ValueCountFrequency (%)
ל14
18.2%
א14
18.2%
ב14
18.2%
ה7
9.1%
י7
9.1%
ע7
9.1%
ש7
9.1%
ת7
9.1%
Hangul
ValueCountFrequency (%)
12
 
8.5%
12
 
8.5%
12
 
8.5%
11
 
7.7%
11
 
7.7%
11
 
7.7%
9
 
6.3%
9
 
6.3%
9
 
6.3%
9
 
6.3%
Other values (5)37
26.1%
Cyrillic
ValueCountFrequency (%)
т3
16.7%
и3
16.7%
о2
11.1%
с2
11.1%
р2
11.1%
И1
 
5.6%
д1
 
5.6%
м1
 
5.6%
в1
 
5.6%
а1
 
5.6%

Adult
Boolean

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing192
Missing (%)0.8%
Memory size199.5 KiB
False
25333 
(Missing)
 
192
ValueCountFrequency (%)
False25333
99.2%
(Missing)192
 
0.8%
2022-10-13T09:32:52.133615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Release
Categorical

HIGH CARDINALITY
MISSING

Distinct665
Distinct (%)2.6%
Missing301
Missing (%)1.2%
Memory size199.5 KiB
2019-06-19
 
300
2019-12-04
 
294
2019-11-20
 
268
2019-07-26
 
243
2021-12-15
 
237
Other values (660)
23882 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters252 240
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)0.4%

Sample

1st row2004-02-11
2nd row2016-06-08
3rd row2001-05-13
4th row2017-11-19
5th row2018-10-24

Common Values

ValueCountFrequency (%)
2019-06-19300
 
1.2%
2019-12-04294
 
1.2%
2019-11-20268
 
1.0%
2019-07-26243
 
1.0%
2021-12-15237
 
0.9%
2022-02-16229
 
0.9%
2021-11-24209
 
0.8%
2022-04-06205
 
0.8%
2021-09-08200
 
0.8%
2019-01-30198
 
0.8%
Other values (655)22841
89.5%
(Missing)301
 
1.2%

Length

2022-10-13T09:32:52.255224image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-06-19300
 
1.2%
2019-12-04294
 
1.2%
2019-11-20268
 
1.1%
2019-07-26243
 
1.0%
2021-12-15237
 
0.9%
2022-02-16229
 
0.9%
2021-11-24209
 
0.8%
2022-04-06205
 
0.8%
2021-09-08200
 
0.8%
2019-01-30198
 
0.8%
Other values (655)22841
90.6%

Most occurring characters

ValueCountFrequency (%)
058512
23.2%
256213
22.3%
-50448
20.0%
140300
16.0%
914785
 
5.9%
86612
 
2.6%
66082
 
2.4%
35142
 
2.0%
44993
 
2.0%
54853
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number201792
80.0%
Dash Punctuation50448
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
058512
29.0%
256213
27.9%
140300
20.0%
914785
 
7.3%
86612
 
3.3%
66082
 
3.0%
35142
 
2.5%
44993
 
2.5%
54853
 
2.4%
74300
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
-50448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common252240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
058512
23.2%
256213
22.3%
-50448
20.0%
140300
16.0%
914785
 
5.9%
86612
 
2.6%
66082
 
2.4%
35142
 
2.0%
44993
 
2.0%
54853
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII252240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
058512
23.2%
256213
22.3%
-50448
20.0%
140300
16.0%
914785
 
5.9%
86612
 
2.6%
66082
 
2.4%
35142
 
2.0%
44993
 
2.0%
54853
 
1.9%

Language
Categorical

HIGH CORRELATION

Distinct34
Distinct (%)0.1%
Missing192
Missing (%)0.8%
Memory size199.5 KiB
fr
12682 
en
11284 
ja
 
293
es
 
266
it
 
152
Other values (29)
 
656

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters50 666
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowfr
2nd rowfr
3rd rowfr
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
fr12682
49.7%
en11284
44.2%
ja293
 
1.1%
es266
 
1.0%
it152
 
0.6%
de143
 
0.6%
da83
 
0.3%
sv60
 
0.2%
fa39
 
0.2%
cs34
 
0.1%
Other values (24)297
 
1.2%
(Missing)192
 
0.8%

Length

2022-10-13T09:32:52.377255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fr12682
50.1%
en11284
44.5%
ja293
 
1.2%
es266
 
1.1%
it152
 
0.6%
de143
 
0.6%
da83
 
0.3%
sv60
 
0.2%
fa39
 
0.2%
cs34
 
0.1%
Other values (24)297
 
1.2%

Most occurring characters

ValueCountFrequency (%)
r12747
25.2%
f12730
25.1%
e11708
23.1%
n11338
22.4%
a435
 
0.9%
s388
 
0.8%
j293
 
0.6%
d234
 
0.5%
t213
 
0.4%
i169
 
0.3%
Other values (16)411
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter50666
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r12747
25.2%
f12730
25.1%
e11708
23.1%
n11338
22.4%
a435
 
0.9%
s388
 
0.8%
j293
 
0.6%
d234
 
0.5%
t213
 
0.4%
i169
 
0.3%
Other values (16)411
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin50666
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r12747
25.2%
f12730
25.1%
e11708
23.1%
n11338
22.4%
a435
 
0.9%
s388
 
0.8%
j293
 
0.6%
d234
 
0.5%
t213
 
0.4%
i169
 
0.3%
Other values (16)411
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII50666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r12747
25.2%
f12730
25.1%
e11708
23.1%
n11338
22.4%
a435
 
0.9%
s388
 
0.8%
j293
 
0.6%
d234
 
0.5%
t213
 
0.4%
i169
 
0.3%
Other values (16)411
 
0.8%

Genre
Categorical

HIGH CARDINALITY
MISSING

Distinct335
Distinct (%)1.3%
Missing685
Missing (%)2.7%
Memory size199.5 KiB
['Comedy']
4114 
['Comedy', 'Drama']
1788 
['Drama']
1694 
['Documentary']
 
503
['Animation', 'Family']
 
497
Other values (330)
16244 

Length

Max length67
Median length56
Mean length26.55583736
Min length9

Characters and Unicode

Total characters659 647
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.1%

Sample

1st row['Animation', 'Adventure', 'Family']
2nd row['Thriller', 'Crime']
3rd row['Documentary']
4th row['Comedy', 'Romance']
5th row['Music', 'Drama', 'History']

Common Values

ValueCountFrequency (%)
['Comedy']4114
 
16.1%
['Comedy', 'Drama']1788
 
7.0%
['Drama']1694
 
6.6%
['Documentary']503
 
2.0%
['Animation', 'Family']497
 
1.9%
['Drama', 'Comedy']493
 
1.9%
['Action', 'Adventure', 'Science Fiction']420
 
1.6%
['Action', 'Adventure', 'Fantasy']351
 
1.4%
['Drama', 'Romance']343
 
1.3%
['Comedy', 'Romance']330
 
1.3%
Other values (325)14307
56.1%
(Missing)685
 
2.7%

Length

2022-10-13T09:32:52.520805image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
comedy12563
20.1%
drama8504
13.6%
adventure6756
10.8%
family5435
8.7%
action4746
 
7.6%
animation4323
 
6.9%
fantasy3527
 
5.6%
thriller2734
 
4.4%
science2606
 
4.2%
fiction2606
 
4.2%
Other values (11)8684
13.9%

Most occurring characters

ValueCountFrequency (%)
'119544
18.1%
e39387
 
6.0%
37644
 
5.7%
a36666
 
5.6%
,34932
 
5.3%
m34823
 
5.3%
i33000
 
5.0%
n31679
 
4.8%
o30271
 
4.6%
r28704
 
4.4%
Other values (22)232997
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter355257
53.9%
Other Punctuation154476
23.4%
Uppercase Letter62590
 
9.5%
Space Separator37644
 
5.7%
Open Punctuation24840
 
3.8%
Close Punctuation24840
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e39387
11.1%
a36666
10.3%
m34823
9.8%
i33000
9.3%
n31679
8.9%
o30271
8.5%
r28704
8.1%
y25020
7.0%
t24917
7.0%
d19319
 
5.4%
Other values (6)51471
14.5%
Uppercase Letter
ValueCountFrequency (%)
A15825
25.3%
C14011
22.4%
F11568
18.5%
D9248
14.8%
T2840
 
4.5%
S2606
 
4.2%
H2286
 
3.7%
R1806
 
2.9%
M1756
 
2.8%
W538
 
0.9%
Other Punctuation
ValueCountFrequency (%)
'119544
77.4%
,34932
 
22.6%
Space Separator
ValueCountFrequency (%)
37644
100.0%
Open Punctuation
ValueCountFrequency (%)
[24840
100.0%
Close Punctuation
ValueCountFrequency (%)
]24840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin417847
63.3%
Common241800
36.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e39387
 
9.4%
a36666
 
8.8%
m34823
 
8.3%
i33000
 
7.9%
n31679
 
7.6%
o30271
 
7.2%
r28704
 
6.9%
y25020
 
6.0%
t24917
 
6.0%
d19319
 
4.6%
Other values (17)114061
27.3%
Common
ValueCountFrequency (%)
'119544
49.4%
37644
 
15.6%
,34932
 
14.4%
[24840
 
10.3%
]24840
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII659647
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'119544
18.1%
e39387
 
6.0%
37644
 
5.7%
a36666
 
5.6%
,34932
 
5.3%
m34823
 
5.3%
i33000
 
5.0%
n31679
 
4.8%
o30271
 
4.6%
r28704
 
4.4%
Other values (22)232997
35.3%

Popularity
Real number (ℝ≥0)

HIGH CORRELATION

Distinct889
Distinct (%)3.5%
Missing192
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean110.0065299
Minimum0.6
Maximum4442.443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:52.847535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile0.968
Q15.661
median12.892
Q398.877
95-th percentile501.133
Maximum4442.443
Range4441.843
Interquartile range (IQR)93.216

Descriptive statistics

Standard deviation283.0022847
Coefficient of variation (CV)2.572595326
Kurtosis53.0691294
Mean110.0065299
Median Absolute Deviation (MAD)11.3
Skewness5.88991168
Sum2786795.422
Variance80090.29313
MonotonicityNot monotonic
2022-10-13T09:32:52.999750image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6799
 
3.1%
0.968210
 
0.8%
125.424192
 
0.8%
184.268174
 
0.7%
308.693166
 
0.7%
91.605152
 
0.6%
98.877147
 
0.6%
1554.919143
 
0.6%
169.484142
 
0.6%
16.868132
 
0.5%
Other values (879)23076
90.4%
(Missing)192
 
0.8%
ValueCountFrequency (%)
0.6799
3.1%
0.60115
 
0.1%
0.6269
 
< 0.1%
0.631
 
< 0.1%
0.6381
 
< 0.1%
0.641
 
< 0.1%
0.6478
 
< 0.1%
0.6511
 
< 0.1%
0.65242
 
0.2%
0.65440
 
0.2%
ValueCountFrequency (%)
4442.44318
 
0.1%
1905.40882
0.3%
1603.24338
 
0.1%
1586.906118
0.5%
1554.919143
0.6%
1450.172106
0.4%
1227.6252
 
< 0.1%
1096.78226
 
0.1%
1022.431106
0.4%
953.98285
0.3%

Vote_average
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct57
Distinct (%)0.2%
Missing1501
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean6.627297702
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:53.171159image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q16
median6.7
Q37.3
95-th percentile8
Maximum10
Range9
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation0.9120148809
Coefficient of variation (CV)0.1376148955
Kurtosis0.8921863338
Mean6.627297702
Median Absolute Deviation (MAD)0.6
Skewness-0.5873811325
Sum159214.2
Variance0.8317711429
MonotonicityNot monotonic
2022-10-13T09:32:53.326084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.71226
 
4.8%
6.51201
 
4.7%
71197
 
4.7%
7.21121
 
4.4%
6.91111
 
4.4%
7.31110
 
4.3%
7.11089
 
4.3%
7.51015
 
4.0%
6.8903
 
3.5%
6.1882
 
3.5%
Other values (47)13169
51.6%
(Missing)1501
 
5.9%
ValueCountFrequency (%)
114
 
0.1%
23
 
< 0.1%
2.72
 
< 0.1%
3.41
 
< 0.1%
3.51
 
< 0.1%
3.611
 
< 0.1%
3.852
 
0.2%
3.929
 
0.1%
4154
0.6%
4.112
 
< 0.1%
ValueCountFrequency (%)
1016
 
0.1%
911
 
< 0.1%
8.75
 
< 0.1%
8.523
 
0.1%
8.4213
0.8%
8.3185
 
0.7%
8.2284
1.1%
8.172
 
0.3%
8466
1.8%
7.9316
1.2%

Vote_count
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct532
Distinct (%)2.2%
Missing1501
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean2152.075341
Minimum1
Maximum32403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:53.478679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q191
median328
Q32827
95-th percentile8440
Maximum32403
Range32402
Interquartile range (IQR)2736

Descriptive statistics

Standard deviation3667.43563
Coefficient of variation (CV)1.704139051
Kurtosis9.548386096
Mean2152.075341
Median Absolute Deviation (MAD)308
Skewness2.745205099
Sum51701458
Variance13450084.1
MonotonicityNot monotonic
2022-10-13T09:32:53.639184image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3280
 
1.1%
145218
 
0.9%
118216
 
0.8%
40198
 
0.8%
28192
 
0.8%
30178
 
0.7%
1176
 
0.7%
8440174
 
0.7%
75173
 
0.7%
53168
 
0.7%
Other values (522)22051
86.4%
(Missing)1501
 
5.9%
ValueCountFrequency (%)
1176
0.7%
2129
0.5%
3280
1.1%
4111
 
0.4%
525
 
0.1%
6113
0.4%
79
 
< 0.1%
876
 
0.3%
9148
0.6%
10168
0.7%
ValueCountFrequency (%)
324033
 
< 0.1%
295003
 
< 0.1%
283721
 
< 0.1%
273827
 
< 0.1%
249273
 
< 0.1%
233273
 
< 0.1%
21885107
0.4%
21380105
0.4%
200181
 
< 0.1%
187856
 
< 0.1%

Overview
Categorical

HIGH CARDINALITY
MISSING

Distinct957
Distinct (%)3.9%
Missing1145
Missing (%)4.5%
Memory size199.5 KiB
Troisième volet des aventures de Sonic, le rapide hérisson bleu...
 
192
Elsa, Anna, Kristoff, Olaf et Sven voyagent bien au‐delà des portes d’Arendelle à la recherche de réponses sur le passé d’Elsa. Cette dernière rencontre un Nokk – un esprit d’eau mythique prenant la forme d’un cheval – qui utilise le pouvoir de l’océan pour protéger les secrets de la forêt.
 
174
Dans ce tout nouvel épisode, la famille Addams va se retrouver emberlificotée dans des aventures complètement déjantées, faites de situations loufoques, face à des personnages à la naïveté désarmante. Quoiqu’il arrive, toujours fidèle aux valeurs qui sont les siennes, la famille Addams ne manquera pas d’y apporter sa touche d’étrangeté et de bizarrerie.
 
166
Le dixième volet de la saga Fast and Furious.
 
152
L’équipe est de retour, mais le jeu a changé. Alors qu’ils retournent dans Jumanji pour secourir l’un des leurs, ils découvrent un monde totalement inattendu. Des déserts arides aux montagnes enneigées, les joueurs vont devoir braver des espaces inconnus et inexplorés, afin de sortir du jeu le plus dangereux du monde...
 
147
Other values (952)
23549 

Length

Max length982
Median length670
Mean length457.2874897
Min length45

Characters and Unicode

Total characters11 148 669
Distinct characters158
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)0.5%

Sample

1st rowEn 1803, sur les côtes des Cornouailles, Le Kid, un gamin de quinze ans, s'échappe de l'orphelinat où il vivait comme un bagnard. Il ignore son vrai nom et a pour seule richesse la carte d'une île au trésor tombée du livre de Black Mór, un célèbre pirate auquel il souhaiterait ressembler. Avec deux pillards d'épaves, Mac Gregor et La Ficelle, Le Kid s'empare du bateau des garde-côtes et se lance à la recherche de la fameuse île à l'autre bout de l'Océan Atlantique. Mais rien ne se passe comme dans les livres de pirates... En quête de son identité, Le Kid est plus fragile qu'on ne le croit, et bien des aventures l'attendent avant d'arriver à l'Ile de Black Mór...
2nd rowPier Ulmann vivote à Paris, entre chantiers et larcins qu’il commet pour le compte de Rachid, sa seule « famille ». Son histoire le rattrape le jour où son père est retrouvé mort dans la rue, après une longue déchéance. Bête noire d’une riche famille de diamantaires basée à Anvers, il ne lui laisse rien, à part l'histoire de son bannissement par les Ulmann et une soif amère de vengeance. Sur l’invitation de son cousin Gabi, Pier se rend à Anvers pour rénover les bureaux de la prestigieuse firme Ulmann. La consigne de Rachid est simple : « Tu vas là-bas pour voir, et pour prendre. » Mais un diamant a beaucoup de facettes…
3rd rowSobibor, 14 octobre 1943, 16 heures : lieu, heure, jour, mois et année de la seule révolte réussie d'un camp d'extermination nazie en Pologne. 365 prisonniers parvinrent à s'évader, mais seuls 47 d'entre eux survécurent aux atrocités de la guerre. Claude Lanzmann a rencontré Yehuda Lerner pendant le tournage de Shoah, à Jérusalem en 1979. Dans ce documentaire, ce dernier s'est confié au réalisateur.
4th rowLorsqu'un jeune couple attrape la redoutable grippe du raton laveur après après avoir emménagé ensemble, ce petit rhume inoffensif se transforme rapidement en guerre totale.
5th rowLe parcours de Queen et son leader Freddie Mercury, de la formation du groupe à son apparition au concert Live Aid en 1985.

Common Values

ValueCountFrequency (%)
Troisième volet des aventures de Sonic, le rapide hérisson bleu...192
 
0.8%
Elsa, Anna, Kristoff, Olaf et Sven voyagent bien au‐delà des portes d’Arendelle à la recherche de réponses sur le passé d’Elsa. Cette dernière rencontre un Nokk – un esprit d’eau mythique prenant la forme d’un cheval – qui utilise le pouvoir de l’océan pour protéger les secrets de la forêt.174
 
0.7%
Dans ce tout nouvel épisode, la famille Addams va se retrouver emberlificotée dans des aventures complètement déjantées, faites de situations loufoques, face à des personnages à la naïveté désarmante. Quoiqu’il arrive, toujours fidèle aux valeurs qui sont les siennes, la famille Addams ne manquera pas d’y apporter sa touche d’étrangeté et de bizarrerie.166
 
0.7%
Le dixième volet de la saga Fast and Furious.152
 
0.6%
L’équipe est de retour, mais le jeu a changé. Alors qu’ils retournent dans Jumanji pour secourir l’un des leurs, ils découvrent un monde totalement inattendu. Des déserts arides aux montagnes enneigées, les joueurs vont devoir braver des espaces inconnus et inexplorés, afin de sortir du jeu le plus dangereux du monde...147
 
0.6%
Après avoir été l’un des meilleurs pilotes de chasse de l'Aéronavale américaine pendant plus de trente ans, Pete “Maverick" Mitchell continue à repousser ses limites en tant que pilote d'essai. Il refuse de monter en grade, car cela l’obligerait à renoncer à voler. Il est chargé de former un détachement de jeunes diplômés de l’école Top Gun pour une mission spéciale qu’aucun pilote n'aurait jamais imaginée. Lors de cette mission, Maverick rencontre le lieutenant Bradley “Rooster” Bradshaw, le fils de son défunt ami, le navigateur Nick “Goose” Bradshaw. Face à un avenir incertain, hanté par ses fantômes, Maverick va devoir affronter ses pires cauchemars au cours d’une mission qui exigera les plus grands sacrifices.143
 
0.6%
Woody a toujours privilégié la joie et le bien‐être de ses jeunes propriétaires – Andy puis Bonnie – et de ses compagnons, n’hésitant pas à prendre tous les risques pour eux, aussi inconsidérés soient‐ils. L’arrivée de Forky, un nouveau jouet qui ne veut pas en être un dans la chambre de Bonnie, met toute la petite bande en émoi. C’est le début d’une grande aventure et d’un extraordinaire voyage pour Woody et ses amis. Le cowboy va découvrir à quel point le monde peut être vaste pour un jouet…142
 
0.6%
Le retour des familles Verneuil et Koffi au grand complet ! Claude et Marie Verneuil font face à une nouvelle crise. Leurs quatre gendres, Rachid, David, Chao et Charles sont décidés à quitter la France avec femmes et enfants pour tenter leur chance à l’étranger. Incapables d’imaginer leur famille loin d’eux, Claude et Marie sont prêts à tout pour les retenir. De leur côté, les Koffi débarquent en France pour le mariage de leur fille. Eux non plus ne sont pas au bout de leurs surprises…132
 
0.5%
Environ un an après la mort de Luke Skywalker, la Résistance tente de survivre face au Premier Ordre, désormais mené par un nouveau Suprême Leader, Kylo Ren. Une rumeur agite cependant toute la galaxie : l'Empereur Palpatine serait de retour. Tandis que Rey s'entraîne sous la houlette de la générale Leia Organa, Kylo Ren cherche à défier Palpatine, qu'il considère comme une menace à son pouvoir.132
 
0.5%
Mia a 11 ans quand elle noue une relation hors du commun avec Charlie, un lionceau blanc né dans la ferme d'élevage de félins de ses parents en Afrique du Sud. Pendant trois ans, ils vont grandir ensemble et vivre une amitié fusionnelle. Quand Mia atteint l'âge de 14 ans et que Charlie est devenu un magnifique lion adulte, elle découvre l’insoutenable vérité: son père a décidé de le vendre à des chasseurs de trophées. Désespérée, Mia n’a pas d’autre choix que de fuir avec Charlie pour le sauver.129
 
0.5%
Other values (947)22871
89.6%
(Missing)1145
 
4.5%

Length

2022-10-13T09:32:53.824145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de95439
 
5.2%
la51515
 
2.8%
et50972
 
2.8%
à39023
 
2.1%
le38706
 
2.1%
les28494
 
1.5%
un27456
 
1.5%
une23921
 
1.3%
pour20930
 
1.1%
son20926
 
1.1%
Other values (13420)1454910
78.5%

Most occurring characters

ValueCountFrequency (%)
1828105
16.4%
e1333113
12.0%
s673665
 
6.0%
a665683
 
6.0%
r665585
 
6.0%
n652213
 
5.9%
i587389
 
5.3%
t559168
 
5.0%
u535772
 
4.8%
l492865
 
4.4%
Other values (148)3155111
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8667629
77.7%
Space Separator1830346
 
16.4%
Other Punctuation281181
 
2.5%
Uppercase Letter240886
 
2.2%
Final Punctuation72713
 
0.7%
Decimal Number29330
 
0.3%
Dash Punctuation18830
 
0.2%
Initial Punctuation3380
 
< 0.1%
Open Punctuation1243
 
< 0.1%
Close Punctuation1243
 
< 0.1%
Other values (3)1888
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1333113
15.4%
s673665
 
7.8%
a665683
 
7.7%
r665585
 
7.7%
n652213
 
7.5%
i587389
 
6.8%
t559168
 
6.5%
u535772
 
6.2%
l492865
 
5.7%
o456501
 
5.3%
Other values (61)2045675
23.6%
Uppercase Letter
ValueCountFrequency (%)
L22695
 
9.4%
M22305
 
9.3%
A21811
 
9.1%
C20121
 
8.4%
P16779
 
7.0%
S16273
 
6.8%
D12666
 
5.3%
E11335
 
4.7%
B10613
 
4.4%
T9762
 
4.1%
Other values (24)76526
31.8%
Decimal Number
ValueCountFrequency (%)
16504
22.2%
05056
17.2%
23399
11.6%
93105
10.6%
42325
 
7.9%
31907
 
6.5%
71900
 
6.5%
81842
 
6.3%
51646
 
5.6%
61359
 
4.6%
Other values (7)287
 
1.0%
Other Punctuation
ValueCountFrequency (%)
,127534
45.4%
.90339
32.1%
'35213
 
12.5%
:8371
 
3.0%
8178
 
2.9%
!4803
 
1.7%
?3561
 
1.3%
"1963
 
0.7%
/781
 
0.3%
;330
 
0.1%
Other values (3)108
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
́690
62.3%
̀268
 
24.2%
̂83
 
7.5%
̧49
 
4.4%
̈17
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
-16041
85.2%
1445
 
7.7%
1334
 
7.1%
10
 
0.1%
Space Separator
ValueCountFrequency (%)
1828105
99.9%
 1881
 
0.1%
360
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
69443
95.5%
»2922
 
4.0%
348
 
0.5%
Initial Punctuation
ValueCountFrequency (%)
«2888
85.4%
491
 
14.5%
1
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$39
54.9%
32
45.1%
Open Punctuation
ValueCountFrequency (%)
(1243
100.0%
Close Punctuation
ValueCountFrequency (%)
)1243
100.0%
Control
ValueCountFrequency (%)
710
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8907367
79.9%
Common2240195
 
20.1%
Inherited1107
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1333113
15.0%
s673665
 
7.6%
a665683
 
7.5%
r665585
 
7.5%
n652213
 
7.3%
i587389
 
6.6%
t559168
 
6.3%
u535772
 
6.0%
l492865
 
5.5%
o456501
 
5.1%
Other values (77)2285413
25.7%
Common
ValueCountFrequency (%)
1828105
81.6%
,127534
 
5.7%
.90339
 
4.0%
69443
 
3.1%
'35213
 
1.6%
-16041
 
0.7%
:8371
 
0.4%
8178
 
0.4%
16504
 
0.3%
05056
 
0.2%
Other values (56)45411
 
2.0%
Inherited
ValueCountFrequency (%)
́690
62.3%
̀268
 
24.2%
̂83
 
7.5%
̧49
 
4.4%
̈17
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII10752150
96.4%
None312335
 
2.8%
Punctuation81610
 
0.7%
Math Alphanum1435
 
< 0.1%
Diacriticals1107
 
< 0.1%
Currency Symbols32
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1828105
17.0%
e1333113
12.4%
s673665
 
6.3%
a665683
 
6.2%
r665585
 
6.2%
n652213
 
6.1%
i587389
 
5.5%
t559168
 
5.2%
u535772
 
5.0%
l492865
 
4.6%
Other values (70)2758592
25.7%
None
ValueCountFrequency (%)
é180367
57.7%
à40441
 
12.9%
è37055
 
11.9%
ê15475
 
5.0%
ô5886
 
1.9%
î4194
 
1.3%
ç3863
 
1.2%
â3457
 
1.1%
ù3205
 
1.0%
»2922
 
0.9%
Other values (28)15470
 
5.0%
Punctuation
ValueCountFrequency (%)
69443
85.1%
8178
 
10.0%
1445
 
1.8%
1334
 
1.6%
491
 
0.6%
360
 
0.4%
348
 
0.4%
10
 
< 0.1%
1
 
< 0.1%
Diacriticals
ValueCountFrequency (%)
́690
62.3%
̀268
 
24.2%
̂83
 
7.5%
̧49
 
4.4%
̈17
 
1.5%
Math Alphanum
ValueCountFrequency (%)
𝐭164
 
11.4%
𝐧82
 
5.7%
𝐦82
 
5.7%
𝐢82
 
5.7%
𝐬82
 
5.7%
𝐫82
 
5.7%
𝐨82
 
5.7%
𝐞82
 
5.7%
𝐚41
 
2.9%
𝟑41
 
2.9%
Other values (15)615
42.9%
Currency Symbols
ValueCountFrequency (%)
32
100.0%

Température maximale
Categorical

HIGH CORRELATION
MISSING

Distinct44
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
 
1446
14°
 
1142
18°
 
1112
12°
 
1097
 
1053
Other values (39)
18337 

Length

Max length3
Median length3
Mean length2.748377227
Min length2

Characters and Unicode

Total characters66 475
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
1446
 
5.7%
14°1142
 
4.5%
18°1112
 
4.4%
12°1097
 
4.3%
1053
 
4.1%
10°1020
 
4.0%
13°934
 
3.7%
20°882
 
3.5%
837
 
3.3%
29°817
 
3.2%
Other values (34)13847
54.2%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:53.980471image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1446
 
6.0%
14°1142
 
4.7%
18°1112
 
4.6%
12°1097
 
4.5%
1053
 
4.4%
10°1020
 
4.2%
13°934
 
3.9%
20°882
 
3.6%
837
 
3.5%
29°817
 
3.4%
Other values (32)13847
57.2%

Most occurring characters

ValueCountFrequency (%)
°24187
36.4%
111042
16.6%
29213
 
13.9%
34593
 
6.9%
83089
 
4.6%
92565
 
3.9%
42548
 
3.8%
72476
 
3.7%
02319
 
3.5%
52230
 
3.4%
Other values (2)2213
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number42263
63.6%
Other Symbol24187
36.4%
Dash Punctuation25
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
111042
26.1%
29213
21.8%
34593
10.9%
83089
 
7.3%
92565
 
6.1%
42548
 
6.0%
72476
 
5.9%
02319
 
5.5%
52230
 
5.3%
62188
 
5.2%
Other Symbol
ValueCountFrequency (%)
°24187
100.0%
Dash Punctuation
ValueCountFrequency (%)
-25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common66475
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
°24187
36.4%
111042
16.6%
29213
 
13.9%
34593
 
6.9%
83089
 
4.6%
92565
 
3.9%
42548
 
3.8%
72476
 
3.7%
02319
 
3.5%
52230
 
3.4%
Other values (2)2213
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII42288
63.6%
None24187
36.4%

Most frequent character per block

None
ValueCountFrequency (%)
°24187
100.0%
ASCII
ValueCountFrequency (%)
111042
26.1%
29213
21.8%
34593
10.9%
83089
 
7.3%
92565
 
6.1%
42548
 
6.0%
72476
 
5.9%
02319
 
5.5%
52230
 
5.3%
62188
 
5.2%

Température minimale
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)0.1%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
 
1329
 
1324
14°
 
1269
 
1254
 
1252
Other values (28)
17759 

Length

Max length3
Median length3
Mean length2.536362509
Min length2

Characters and Unicode

Total characters61 347
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
1329
 
5.2%
1324
 
5.2%
14°1269
 
5.0%
1254
 
4.9%
1252
 
4.9%
13°1193
 
4.7%
-1°1130
 
4.4%
1113
 
4.4%
12°1097
 
4.3%
1084
 
4.2%
Other values (23)12142
47.6%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.096267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2384
 
9.9%
1891
 
7.8%
1829
 
7.6%
1748
 
7.2%
1465
 
6.1%
1279
 
5.3%
14°1269
 
5.2%
13°1193
 
4.9%
1113
 
4.6%
12°1097
 
4.5%
Other values (15)8919
36.9%

Most occurring characters

ValueCountFrequency (%)
°24187
39.4%
112297
20.0%
23807
 
6.2%
-3528
 
5.8%
43152
 
5.1%
33001
 
4.9%
02255
 
3.7%
52179
 
3.6%
72123
 
3.5%
62035
 
3.3%
Other values (2)2783
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number33632
54.8%
Other Symbol24187
39.4%
Dash Punctuation3528
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
112297
36.6%
23807
 
11.3%
43152
 
9.4%
33001
 
8.9%
02255
 
6.7%
52179
 
6.5%
72123
 
6.3%
62035
 
6.1%
81463
 
4.4%
91320
 
3.9%
Other Symbol
ValueCountFrequency (%)
°24187
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3528
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common61347
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
°24187
39.4%
112297
20.0%
23807
 
6.2%
-3528
 
5.8%
43152
 
5.1%
33001
 
4.9%
02255
 
3.7%
52179
 
3.6%
72123
 
3.5%
62035
 
3.3%
Other values (2)2783
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII37160
60.6%
None24187
39.4%

Most frequent character per block

None
ValueCountFrequency (%)
°24187
100.0%
ASCII
ValueCountFrequency (%)
112297
33.1%
23807
 
10.2%
-3528
 
9.5%
43152
 
8.5%
33001
 
8.1%
02255
 
6.1%
52179
 
5.9%
72123
 
5.7%
62035
 
5.5%
81463
 
3.9%

Vitesse du vent
Categorical

HIGH CORRELATION
MISSING

Distinct38
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
9km/h
2339 
6km/h
2283 
8km/h
2213 
10km/h
2100 
7km/h
1801 
Other values (33)
13451 

Length

Max length6
Median length6
Mean length5.569107372
Min length5

Characters and Unicode

Total characters134 700
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19km/h
2nd row19km/h
3rd row19km/h
4th row19km/h
5th row19km/h

Common Values

ValueCountFrequency (%)
9km/h2339
 
9.2%
6km/h2283
 
8.9%
8km/h2213
 
8.7%
10km/h2100
 
8.2%
7km/h1801
 
7.1%
11km/h1259
 
4.9%
13km/h1230
 
4.8%
5km/h1202
 
4.7%
15km/h1189
 
4.7%
14km/h1110
 
4.3%
Other values (28)7461
29.2%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.228824image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9km/h2339
 
9.7%
6km/h2283
 
9.4%
8km/h2213
 
9.1%
10km/h2100
 
8.7%
7km/h1801
 
7.4%
11km/h1259
 
5.2%
13km/h1230
 
5.1%
5km/h1202
 
5.0%
15km/h1189
 
4.9%
14km/h1110
 
4.6%
Other values (28)7461
30.8%

Most occurring characters

ValueCountFrequency (%)
k24187
18.0%
m24187
18.0%
/24187
18.0%
h24187
18.0%
112569
9.3%
24004
 
3.0%
63154
 
2.3%
93145
 
2.3%
83045
 
2.3%
72886
 
2.1%
Other values (4)9149
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter72561
53.9%
Decimal Number37952
28.2%
Other Punctuation24187
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
112569
33.1%
24004
 
10.6%
63154
 
8.3%
93145
 
8.3%
83045
 
8.0%
72886
 
7.6%
02575
 
6.8%
52488
 
6.6%
42047
 
5.4%
32039
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
k24187
33.3%
m24187
33.3%
h24187
33.3%
Other Punctuation
ValueCountFrequency (%)
/24187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin72561
53.9%
Common62139
46.1%

Most frequent character per script

Common
ValueCountFrequency (%)
/24187
38.9%
112569
20.2%
24004
 
6.4%
63154
 
5.1%
93145
 
5.1%
83045
 
4.9%
72886
 
4.6%
02575
 
4.1%
52488
 
4.0%
42047
 
3.3%
Latin
ValueCountFrequency (%)
k24187
33.3%
m24187
33.3%
h24187
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII134700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k24187
18.0%
m24187
18.0%
/24187
18.0%
h24187
18.0%
112569
9.3%
24004
 
3.0%
63154
 
2.3%
93145
 
2.3%
83045
 
2.3%
72886
 
2.1%
Other values (4)9149
 
6.8%

Température du vent
Categorical

HIGH CORRELATION
MISSING

Distinct37
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
 
1348
 
1259
14°
 
1212
-2°
 
1183
12°
 
1054
Other values (32)
18131 

Length

Max length4
Median length3
Mean length2.599454252
Min length2

Characters and Unicode

Total characters62 873
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-2°
2nd row-2°
3rd row-2°
4th row-2°
5th row-2°

Common Values

ValueCountFrequency (%)
1348
 
5.3%
1259
 
4.9%
14°1212
 
4.7%
-2°1183
 
4.6%
12°1054
 
4.1%
1009
 
4.0%
963
 
3.8%
936
 
3.7%
927
 
3.6%
-1°924
 
3.6%
Other values (27)13372
52.4%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.378474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2442
 
10.1%
2167
 
9.0%
1933
 
8.0%
1784
 
7.4%
1516
 
6.3%
1411
 
5.8%
14°1212
 
5.0%
1193
 
4.9%
1139
 
4.7%
12°1105
 
4.6%
Other values (15)8285
34.3%

Most occurring characters

ValueCountFrequency (%)
°24187
38.5%
110868
17.3%
-5827
 
9.3%
24366
 
6.9%
43433
 
5.5%
32627
 
4.2%
52289
 
3.6%
62279
 
3.6%
02141
 
3.4%
72013
 
3.2%
Other values (2)2843
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32859
52.3%
Other Symbol24187
38.5%
Dash Punctuation5827
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
110868
33.1%
24366
13.3%
43433
 
10.4%
32627
 
8.0%
52289
 
7.0%
62279
 
6.9%
02141
 
6.5%
72013
 
6.1%
81613
 
4.9%
91230
 
3.7%
Other Symbol
ValueCountFrequency (%)
°24187
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5827
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common62873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
°24187
38.5%
110868
17.3%
-5827
 
9.3%
24366
 
6.9%
43433
 
5.5%
32627
 
4.2%
52289
 
3.6%
62279
 
3.6%
02141
 
3.4%
72013
 
3.2%
Other values (2)2843
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII38686
61.5%
None24187
38.5%

Most frequent character per block

None
ValueCountFrequency (%)
°24187
100.0%
ASCII
ValueCountFrequency (%)
110868
28.1%
-5827
15.1%
24366
11.3%
43433
 
8.9%
32627
 
6.8%
52289
 
5.9%
62279
 
5.9%
02141
 
5.5%
72013
 
5.2%
81613
 
4.2%

Précipitations
Categorical

HIGH CORRELATION
MISSING

Distinct35
Distinct (%)0.2%
Missing6460
Missing (%)25.3%
Memory size199.5 KiB
1mm
6212 
0mm
5513 
2mm
1857 
3mm
1111 
4mm
832 
Other values (30)
3540 

Length

Max length4
Median length3
Mean length3.082192499
Min length3

Characters and Unicode

Total characters58 762
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5mm
2nd row5mm
3rd row5mm
4th row5mm
5th row5mm

Common Values

ValueCountFrequency (%)
1mm6212
24.3%
0mm5513
21.6%
2mm1857
 
7.3%
3mm1111
 
4.4%
4mm832
 
3.3%
5mm549
 
2.2%
6mm509
 
2.0%
7mm463
 
1.8%
8mm247
 
1.0%
9mm205
 
0.8%
Other values (25)1567
 
6.1%
(Missing)6460
25.3%

Length

2022-10-13T09:32:54.529643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1mm6212
32.6%
0mm5513
28.9%
2mm1857
 
9.7%
3mm1111
 
5.8%
4mm832
 
4.4%
5mm549
 
2.9%
6mm509
 
2.7%
7mm463
 
2.4%
8mm247
 
1.3%
9mm205
 
1.1%
Other values (25)1567
 
8.2%

Most occurring characters

ValueCountFrequency (%)
m38130
64.9%
17196
 
12.2%
05711
 
9.7%
22599
 
4.4%
31417
 
2.4%
41062
 
1.8%
5726
 
1.2%
6677
 
1.2%
7590
 
1.0%
9335
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38130
64.9%
Decimal Number20632
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
17196
34.9%
05711
27.7%
22599
 
12.6%
31417
 
6.9%
41062
 
5.1%
5726
 
3.5%
6677
 
3.3%
7590
 
2.9%
9335
 
1.6%
8319
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
m38130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin38130
64.9%
Common20632
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
17196
34.9%
05711
27.7%
22599
 
12.6%
31417
 
6.9%
41062
 
5.1%
5726
 
3.5%
6677
 
3.3%
7590
 
2.9%
9335
 
1.6%
8319
 
1.5%
Latin
ValueCountFrequency (%)
m38130
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII58762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m38130
64.9%
17196
 
12.2%
05711
 
9.7%
22599
 
4.4%
31417
 
2.4%
41062
 
1.8%
5726
 
1.2%
6677
 
1.2%
7590
 
1.0%
9335
 
0.6%

Humidité
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct55
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
93%
 
1654
92%
 
1560
96%
 
1500
94%
 
1497
91%
 
1394
Other values (50)
16582 

Length

Max length4
Median length3
Mean length3.005002687
Min length3

Characters and Unicode

Total characters72 682
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row91%
2nd row91%
3rd row91%
4th row91%
5th row91%

Common Values

ValueCountFrequency (%)
93%1654
 
6.5%
92%1560
 
6.1%
96%1500
 
5.9%
94%1497
 
5.9%
91%1394
 
5.5%
90%1255
 
4.9%
95%1205
 
4.7%
97%1184
 
4.6%
89%1094
 
4.3%
88%1056
 
4.1%
Other values (45)10788
42.3%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.649818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
931654
 
6.8%
921560
 
6.4%
961500
 
6.2%
941497
 
6.2%
911394
 
5.8%
901255
 
5.2%
951205
 
5.0%
971184
 
4.9%
891094
 
4.5%
881056
 
4.4%
Other values (45)10788
44.6%

Most occurring characters

ValueCountFrequency (%)
%24187
33.3%
914585
20.1%
89124
 
12.6%
75201
 
7.2%
64268
 
5.9%
52879
 
4.0%
42765
 
3.8%
22564
 
3.5%
32486
 
3.4%
12444
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number48495
66.7%
Other Punctuation24187
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
914585
30.1%
89124
18.8%
75201
 
10.7%
64268
 
8.8%
52879
 
5.9%
42765
 
5.7%
22564
 
5.3%
32486
 
5.1%
12444
 
5.0%
02179
 
4.5%
Other Punctuation
ValueCountFrequency (%)
%24187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common72682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
%24187
33.3%
914585
20.1%
89124
 
12.6%
75201
 
7.2%
64268
 
5.9%
52879
 
4.0%
42765
 
3.8%
22564
 
3.5%
32486
 
3.4%
12444
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII72682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
%24187
33.3%
914585
20.1%
89124
 
12.6%
75201
 
7.2%
64268
 
5.9%
52879
 
4.0%
42765
 
3.8%
22564
 
3.5%
32486
 
3.4%
12444
 
3.4%

Visibilité
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
10km
9551 
9km
1710 
9.875km
1145 
8km
1018 
9.625km
 
769
Other values (49)
9994 

Length

Max length7
Median length6
Mean length4.969156985
Min length3

Characters and Unicode

Total characters120 189
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9.375km
2nd row9.375km
3rd row9.375km
4th row9.375km
5th row9.375km

Common Values

ValueCountFrequency (%)
10km9551
37.4%
9km1710
 
6.7%
9.875km1145
 
4.5%
8km1018
 
4.0%
9.625km769
 
3.0%
9.75km657
 
2.6%
7km617
 
2.4%
8.625km610
 
2.4%
8.875km610
 
2.4%
7.75km533
 
2.1%
Other values (44)6967
27.3%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.771800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10km9551
39.5%
9km1710
 
7.1%
9.875km1145
 
4.7%
8km1018
 
4.2%
9.625km769
 
3.2%
9.75km657
 
2.7%
7km617
 
2.6%
8.625km610
 
2.5%
8.875km610
 
2.5%
7.75km533
 
2.2%
Other values (44)6967
28.8%

Most occurring characters

ValueCountFrequency (%)
k24187
20.1%
m24187
20.1%
511651
9.7%
.11044
9.2%
110192
8.5%
09551
 
7.9%
78015
 
6.7%
85883
 
4.9%
95717
 
4.8%
24132
 
3.4%
Other values (3)5630
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number60771
50.6%
Lowercase Letter48374
40.2%
Other Punctuation11044
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
511651
19.2%
110192
16.8%
09551
15.7%
78015
13.2%
85883
9.7%
95717
9.4%
24132
 
6.8%
64068
 
6.7%
31273
 
2.1%
4289
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
k24187
50.0%
m24187
50.0%
Other Punctuation
ValueCountFrequency (%)
.11044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common71815
59.8%
Latin48374
40.2%

Most frequent character per script

Common
ValueCountFrequency (%)
511651
16.2%
.11044
15.4%
110192
14.2%
09551
13.3%
78015
11.2%
85883
8.2%
95717
8.0%
24132
 
5.8%
64068
 
5.7%
31273
 
1.8%
Latin
ValueCountFrequency (%)
k24187
50.0%
m24187
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII120189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k24187
20.1%
m24187
20.1%
511651
9.7%
.11044
9.2%
110192
8.5%
09551
 
7.9%
78015
 
6.7%
85883
 
4.9%
95717
 
4.8%
24132
 
3.4%
Other values (3)5630
 
4.7%

Couverture nuageuse
Categorical

HIGH CARDINALITY
MISSING

Distinct101
Distinct (%)0.4%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
5%
 
545
8%
 
505
7%
 
444
70%
 
443
34%
 
397
Other values (96)
21853 

Length

Max length4
Median length3
Mean length2.860007442
Min length2

Characters and Unicode

Total characters69 175
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row73%
2nd row73%
3rd row73%
4th row73%
5th row73%

Common Values

ValueCountFrequency (%)
5%545
 
2.1%
8%505
 
2.0%
7%444
 
1.7%
70%443
 
1.7%
34%397
 
1.6%
2%393
 
1.5%
16%388
 
1.5%
9%386
 
1.5%
3%368
 
1.4%
15%356
 
1.4%
Other values (91)19962
78.2%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:54.905904image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5545
 
2.3%
8505
 
2.1%
7444
 
1.8%
70443
 
1.8%
34397
 
1.6%
2393
 
1.6%
16388
 
1.6%
9386
 
1.6%
3368
 
1.5%
15356
 
1.5%
Other values (91)19962
82.5%

Most occurring characters

ValueCountFrequency (%)
%24187
35.0%
15665
 
8.2%
45049
 
7.3%
25030
 
7.3%
54802
 
6.9%
74706
 
6.8%
64516
 
6.5%
34428
 
6.4%
84345
 
6.3%
93555
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number44988
65.0%
Other Punctuation24187
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
15665
12.6%
45049
11.2%
25030
11.2%
54802
10.7%
74706
10.5%
64516
10.0%
34428
9.8%
84345
9.7%
93555
7.9%
02892
6.4%
Other Punctuation
ValueCountFrequency (%)
%24187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common69175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
%24187
35.0%
15665
 
8.2%
45049
 
7.3%
25030
 
7.3%
54802
 
6.9%
74706
 
6.8%
64516
 
6.5%
34428
 
6.4%
84345
 
6.3%
93555
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII69175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
%24187
35.0%
15665
 
8.2%
45049
 
7.3%
25030
 
7.3%
54802
 
6.9%
74706
 
6.8%
64516
 
6.5%
34428
 
6.4%
84345
 
6.3%
93555
 
5.1%

Indice de chaleur
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean17.17691322
Minimum0
Maximum42
Zeros78
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:55.058078image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median16
Q325
95-th percentile32
Maximum42
Range42
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.096849254
Coefficient of variation (CV)0.5295974392
Kurtosis-0.8827602231
Mean17.17691322
Median Absolute Deviation (MAD)8
Skewness0.2954057489
Sum415458
Variance82.75266635
MonotonicityNot monotonic
2022-10-13T09:32:55.192940image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
81417
 
5.6%
251362
 
5.3%
181141
 
4.5%
141133
 
4.4%
261085
 
4.3%
91082
 
4.2%
121067
 
4.2%
10966
 
3.8%
13959
 
3.8%
7944
 
3.7%
Other values (32)13031
51.1%
(Missing)1338
 
5.2%
ValueCountFrequency (%)
078
 
0.3%
1106
 
0.4%
2233
 
0.9%
3592
2.3%
4487
 
1.9%
5598
2.3%
6574
2.2%
7944
3.7%
81417
5.6%
91082
4.2%
ValueCountFrequency (%)
4224
 
0.1%
4055
 
0.2%
3966
 
0.3%
38119
 
0.5%
3774
 
0.3%
36214
0.8%
35103
 
0.4%
34218
0.9%
33299
1.2%
32436
1.7%

Point de rosée
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)0.1%
Missing1823
Missing (%)7.1%
Memory size199.5 KiB
7°C
1631 
4°C
1631 
5°C
 
1534
6°C
 
1396
13°C
 
1374
Other values (19)
16136 

Length

Max length4
Median length3
Mean length3.465361573
Min length3

Characters and Unicode

Total characters82 136
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2°C
2nd row2°C
3rd row2°C
4th row2°C
5th row2°C

Common Values

ValueCountFrequency (%)
7°C1631
 
6.4%
4°C1631
 
6.4%
5°C1534
 
6.0%
6°C1396
 
5.5%
13°C1374
 
5.4%
16°C1276
 
5.0%
14°C1240
 
4.9%
0°C1240
 
4.9%
10°C1179
 
4.6%
15°C1148
 
4.5%
Other values (14)10053
39.4%
(Missing)1823
 
7.1%

Length

2022-10-13T09:32:55.335339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
7°c1631
 
6.9%
4°c1631
 
6.9%
5°c1534
 
6.5%
6°c1396
 
5.9%
13°c1374
 
5.8%
16°c1276
 
5.4%
14°c1240
 
5.2%
0°c1240
 
5.2%
10°c1179
 
5.0%
15°c1148
 
4.8%
Other values (14)10053
42.4%

Most occurring characters

ValueCountFrequency (%)
°23702
28.9%
C23702
28.9%
112718
15.5%
42895
 
3.5%
22854
 
3.5%
02718
 
3.3%
52682
 
3.3%
62672
 
3.3%
72659
 
3.2%
32314
 
2.8%
Other values (2)3220
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number34732
42.3%
Other Symbol23702
28.9%
Uppercase Letter23702
28.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
112718
36.6%
42895
 
8.3%
22854
 
8.2%
02718
 
7.8%
52682
 
7.7%
62672
 
7.7%
72659
 
7.7%
32314
 
6.7%
81743
 
5.0%
91477
 
4.3%
Other Symbol
ValueCountFrequency (%)
°23702
100.0%
Uppercase Letter
ValueCountFrequency (%)
C23702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common58434
71.1%
Latin23702
28.9%

Most frequent character per script

Common
ValueCountFrequency (%)
°23702
40.6%
112718
21.8%
42895
 
5.0%
22854
 
4.9%
02718
 
4.7%
52682
 
4.6%
62672
 
4.6%
72659
 
4.6%
32314
 
4.0%
81743
 
3.0%
Latin
ValueCountFrequency (%)
C23702
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII58434
71.1%
None23702
28.9%

Most frequent character per block

None
ValueCountFrequency (%)
°23702
100.0%
ASCII
ValueCountFrequency (%)
C23702
40.6%
112718
21.8%
42895
 
5.0%
22854
 
4.9%
02718
 
4.7%
52682
 
4.6%
62672
 
4.6%
72659
 
4.6%
32314
 
4.0%
81743
 
3.0%

Pression
Categorical

HIGH CORRELATION
MISSING

Distinct43
Distinct (%)0.2%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
1022hPa
1689 
1020hPa
1686 
1017hPa
1641 
1019hPa
 
1566
1018hPa
 
1493
Other values (38)
16112 

Length

Max length7
Median length7
Mean length6.996816472
Min length6

Characters and Unicode

Total characters169 232
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1023hPa
2nd row1023hPa
3rd row1023hPa
4th row1023hPa
5th row1023hPa

Common Values

ValueCountFrequency (%)
1022hPa1689
 
6.6%
1020hPa1686
 
6.6%
1017hPa1641
 
6.4%
1019hPa1566
 
6.1%
1018hPa1493
 
5.8%
1023hPa1430
 
5.6%
1024hPa1377
 
5.4%
1021hPa1315
 
5.2%
1026hPa1118
 
4.4%
1016hPa1036
 
4.1%
Other values (33)9836
38.5%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:55.447461image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1022hpa1689
 
7.0%
1020hpa1686
 
7.0%
1017hpa1641
 
6.8%
1019hpa1566
 
6.5%
1018hpa1493
 
6.2%
1023hpa1430
 
5.9%
1024hpa1377
 
5.7%
1021hpa1315
 
5.4%
1026hpa1118
 
4.6%
1016hpa1036
 
4.3%
Other values (33)9836
40.7%

Most occurring characters

ValueCountFrequency (%)
134974
20.7%
027774
16.4%
h24187
14.3%
P24187
14.3%
a24187
14.3%
214262
8.4%
35148
 
3.0%
72712
 
1.6%
62535
 
1.5%
82383
 
1.4%
Other values (3)6883
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number96671
57.1%
Lowercase Letter48374
28.6%
Uppercase Letter24187
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
134974
36.2%
027774
28.7%
214262
14.8%
35148
 
5.3%
72712
 
2.8%
62535
 
2.6%
82383
 
2.5%
42309
 
2.4%
52289
 
2.4%
92285
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
h24187
50.0%
a24187
50.0%
Uppercase Letter
ValueCountFrequency (%)
P24187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common96671
57.1%
Latin72561
42.9%

Most frequent character per script

Common
ValueCountFrequency (%)
134974
36.2%
027774
28.7%
214262
14.8%
35148
 
5.3%
72712
 
2.8%
62535
 
2.6%
82383
 
2.5%
42309
 
2.4%
52289
 
2.4%
92285
 
2.4%
Latin
ValueCountFrequency (%)
h24187
33.3%
P24187
33.3%
a24187
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII169232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134974
20.7%
027774
16.4%
h24187
14.3%
P24187
14.3%
a24187
14.3%
214262
8.4%
35148
 
3.0%
72712
 
1.6%
62535
 
1.5%
82383
 
1.4%
Other values (3)6883
 
4.1%

Heure du lever du soleil
Categorical

HIGH CARDINALITY
MISSING

Distinct210
Distinct (%)0.9%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
04:53:00
 
699
08:21:00
 
664
08:19:00
 
449
08:22:00
 
449
08:20:00
 
397
Other values (205)
21529 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters193 496
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07:57:00
2nd row07:57:00
3rd row07:57:00
4th row07:57:00
5th row07:57:00

Common Values

ValueCountFrequency (%)
04:53:00699
 
2.7%
08:21:00664
 
2.6%
08:19:00449
 
1.8%
08:22:00449
 
1.8%
08:20:00397
 
1.6%
04:54:00327
 
1.3%
05:53:00321
 
1.3%
08:18:00301
 
1.2%
08:16:00275
 
1.1%
08:15:00274
 
1.1%
Other values (200)20031
78.5%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:55.570894image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
04:53:00699
 
2.9%
08:21:00664
 
2.7%
08:19:00449
 
1.9%
08:22:00449
 
1.9%
08:20:00397
 
1.6%
04:54:00327
 
1.4%
05:53:00321
 
1.3%
08:18:00301
 
1.2%
08:16:00275
 
1.1%
08:15:00274
 
1.1%
Other values (200)20031
82.8%

Most occurring characters

ValueCountFrequency (%)
079788
41.2%
:48374
25.0%
513823
 
7.1%
78274
 
4.3%
17743
 
4.0%
87636
 
3.9%
67075
 
3.7%
46704
 
3.5%
26357
 
3.3%
35357
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number145122
75.0%
Other Punctuation48374
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
079788
55.0%
513823
 
9.5%
78274
 
5.7%
17743
 
5.3%
87636
 
5.3%
67075
 
4.9%
46704
 
4.6%
26357
 
4.4%
35357
 
3.7%
92365
 
1.6%
Other Punctuation
ValueCountFrequency (%)
:48374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common193496
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
079788
41.2%
:48374
25.0%
513823
 
7.1%
78274
 
4.3%
17743
 
4.0%
87636
 
3.9%
67075
 
3.7%
46704
 
3.5%
26357
 
3.3%
35357
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII193496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
079788
41.2%
:48374
25.0%
513823
 
7.1%
78274
 
4.3%
17743
 
4.0%
87636
 
3.9%
67075
 
3.7%
46704
 
3.5%
26357
 
3.3%
35357
 
2.8%

Heure du coucher du soleil
Categorical

HIGH CARDINALITY
MISSING

Distinct269
Distinct (%)1.1%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
16:59:00
 
904
20:34:00
 
775
17:00:00
 
458
17:01:00
 
396
20:33:00
 
372
Other values (264)
21282 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters193 496
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row17:02:00
2nd row17:02:00
3rd row17:02:00
4th row17:02:00
5th row17:02:00

Common Values

ValueCountFrequency (%)
16:59:00904
 
3.5%
20:34:00775
 
3.0%
17:00:00458
 
1.8%
17:01:00396
 
1.6%
20:33:00372
 
1.5%
17:02:00337
 
1.3%
20:32:00318
 
1.2%
20:30:00246
 
1.0%
16:58:00243
 
1.0%
21:35:00235
 
0.9%
Other values (259)19903
78.0%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:55.684086image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
16:59:00904
 
3.7%
20:34:00775
 
3.2%
17:00:00458
 
1.9%
17:01:00396
 
1.6%
20:33:00372
 
1.5%
17:02:00337
 
1.4%
20:32:00318
 
1.3%
20:30:00246
 
1.0%
16:58:00243
 
1.0%
21:35:00235
 
1.0%
Other values (259)19903
82.3%

Most occurring characters

ValueCountFrequency (%)
061724
31.9%
:48374
25.0%
124544
 
12.7%
215300
 
7.9%
79084
 
4.7%
37771
 
4.0%
96592
 
3.4%
86098
 
3.2%
55628
 
2.9%
45279
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number145122
75.0%
Other Punctuation48374
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
061724
42.5%
124544
 
16.9%
215300
 
10.5%
79084
 
6.3%
37771
 
5.4%
96592
 
4.5%
86098
 
4.2%
55628
 
3.9%
45279
 
3.6%
63102
 
2.1%
Other Punctuation
ValueCountFrequency (%)
:48374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common193496
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
061724
31.9%
:48374
25.0%
124544
 
12.7%
215300
 
7.9%
79084
 
4.7%
37771
 
4.0%
96592
 
3.4%
86098
 
3.2%
55628
 
2.9%
45279
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII193496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
061724
31.9%
:48374
25.0%
124544
 
12.7%
215300
 
7.9%
79084
 
4.7%
37771
 
4.0%
96592
 
3.4%
86098
 
3.2%
55628
 
2.9%
45279
 
2.7%

Durée du jour
Categorical

HIGH CARDINALITY
MISSING

Distinct372
Distinct (%)1.5%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
8:43:0
 
725
15:40:0
 
501
8:44:0
 
378
15:41:0
 
358
15:38:0
 
314
Other values (367)
21911 

Length

Max length7
Median length7
Mean length6.58663745
Min length5

Characters and Unicode

Total characters159 311
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9:5:0
2nd row9:5:0
3rd row9:5:0
4th row9:5:0
5th row9:5:0

Common Values

ValueCountFrequency (%)
8:43:0725
 
2.8%
15:40:0501
 
2.0%
8:44:0378
 
1.5%
15:41:0358
 
1.4%
15:38:0314
 
1.2%
15:39:0280
 
1.1%
8:47:0231
 
0.9%
8:46:0229
 
0.9%
8:45:0226
 
0.9%
15:36:0220
 
0.9%
Other values (362)20725
81.2%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:55.807111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8:43:0725
 
3.0%
15:40:0501
 
2.1%
8:44:0378
 
1.6%
15:41:0358
 
1.5%
15:38:0314
 
1.3%
15:39:0280
 
1.2%
8:47:0231
 
1.0%
8:46:0229
 
0.9%
8:45:0226
 
0.9%
15:36:0220
 
0.9%
Other values (362)20725
85.7%

Most occurring characters

ValueCountFrequency (%)
:48374
30.4%
029707
18.6%
125967
16.3%
511660
 
7.3%
411129
 
7.0%
39539
 
6.0%
27316
 
4.6%
85628
 
3.5%
95444
 
3.4%
72498
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number110937
69.6%
Other Punctuation48374
30.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029707
26.8%
125967
23.4%
511660
 
10.5%
411129
 
10.0%
39539
 
8.6%
27316
 
6.6%
85628
 
5.1%
95444
 
4.9%
72498
 
2.3%
62049
 
1.8%
Other Punctuation
ValueCountFrequency (%)
:48374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common159311
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
:48374
30.4%
029707
18.6%
125967
16.3%
511660
 
7.3%
411129
 
7.0%
39539
 
6.0%
27316
 
4.6%
85628
 
3.5%
95444
 
3.4%
72498
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII159311
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
:48374
30.4%
029707
18.6%
125967
16.3%
511660
 
7.3%
411129
 
7.0%
39539
 
6.0%
27316
 
4.6%
85628
 
3.5%
95444
 
3.4%
72498
 
1.6%

L'avis de historique-meteo.net
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)< 0.1%
Missing1338
Missing (%)5.2%
Memory size199.5 KiB
très défavorable
9518 
favorable
6922 
correct
3837 
défavorable
3079 
idéal
 
831

Length

Max length16
Median length11
Mean length11.55451275
Min length5

Characters and Unicode

Total characters279 469
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtrès défavorable
2nd rowtrès défavorable
3rd rowtrès défavorable
4th rowtrès défavorable
5th rowtrès défavorable

Common Values

ValueCountFrequency (%)
très défavorable9518
37.3%
favorable6922
27.1%
correct3837
15.0%
défavorable3079
 
12.1%
idéal831
 
3.3%
(Missing)1338
 
5.2%

Length

2022-10-13T09:32:55.939480image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-13T09:32:56.203965image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
défavorable12597
37.4%
très9518
28.2%
favorable6922
20.5%
correct3837
 
11.4%
idéal831
 
2.5%

Most occurring characters

ValueCountFrequency (%)
a39869
14.3%
r36711
13.1%
o23356
8.4%
e23356
8.4%
l20350
7.3%
f19519
 
7.0%
v19519
 
7.0%
b19519
 
7.0%
d13428
 
4.8%
é13428
 
4.8%
Other values (6)50414
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter269951
96.6%
Space Separator9518
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a39869
14.8%
r36711
13.6%
o23356
8.7%
e23356
8.7%
l20350
7.5%
f19519
7.2%
v19519
7.2%
b19519
7.2%
d13428
 
5.0%
é13428
 
5.0%
Other values (5)40896
15.1%
Space Separator
ValueCountFrequency (%)
9518
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin269951
96.6%
Common9518
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a39869
14.8%
r36711
13.6%
o23356
8.7%
e23356
8.7%
l20350
7.5%
f19519
7.2%
v19519
7.2%
b19519
7.2%
d13428
 
5.0%
é13428
 
5.0%
Other values (5)40896
15.1%
Common
ValueCountFrequency (%)
9518
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII256523
91.8%
None22946
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a39869
15.5%
r36711
14.3%
o23356
9.1%
e23356
9.1%
l20350
7.9%
f19519
7.6%
v19519
7.6%
b19519
7.6%
d13428
 
5.2%
t13355
 
5.2%
Other values (4)27541
10.7%
None
ValueCountFrequency (%)
é13428
58.5%
è9518
41.5%

vacances_zone_a
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
False
15611 
True
9914 
ValueCountFrequency (%)
False15611
61.2%
True9914
38.8%
2022-10-13T09:32:56.336031image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

vacances_zone_b
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
False
15668 
True
9857 
ValueCountFrequency (%)
False15668
61.4%
True9857
38.6%
2022-10-13T09:32:56.437872image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

vacances_zone_c
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
False
15796 
True
9729 
ValueCountFrequency (%)
False15796
61.9%
True9729
38.1%
2022-10-13T09:32:56.549417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

nom_vacances
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)0.1%
Missing13851
Missing (%)54.3%
Memory size199.5 KiB
Vacances d'été
4819 
Vacances d'hiver
2486 
Vacances de printemps
1588 
Vacances de Noël
1331 
Vacances de la Toussaint
1233 

Length

Max length24
Median length21
Mean length16.75526812
Min length14

Characters and Unicode

Total characters195 601
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVacances de Noël
2nd rowVacances de Noël
3rd rowVacances de Noël
4th rowVacances de Noël
5th rowVacances de Noël

Common Values

ValueCountFrequency (%)
Vacances d'été4819
 
18.9%
Vacances d'hiver2486
 
9.7%
Vacances de printemps1588
 
6.2%
Vacances de Noël1331
 
5.2%
Vacances de la Toussaint1233
 
4.8%
Pont de l'Ascension217
 
0.9%
(Missing)13851
54.3%

Length

2022-10-13T09:32:56.651107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-13T09:32:56.804521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
vacances11457
39.6%
d'été4819
16.6%
de4369
 
15.1%
d'hiver2486
 
8.6%
printemps1588
 
5.5%
noël1331
 
4.6%
la1233
 
4.3%
toussaint1233
 
4.3%
pont217
 
0.7%
l'ascension217
 
0.7%

Most occurring characters

ValueCountFrequency (%)
a25380
13.0%
c23131
11.8%
e20117
10.3%
17276
8.8%
s15945
8.2%
n14929
 
7.6%
d11674
 
6.0%
V11457
 
5.9%
é9638
 
4.9%
t7857
 
4.0%
Other values (15)38197
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter156348
79.9%
Space Separator17276
 
8.8%
Uppercase Letter14455
 
7.4%
Other Punctuation7522
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a25380
16.2%
c23131
14.8%
e20117
12.9%
s15945
10.2%
n14929
9.5%
d11674
7.5%
é9638
 
6.2%
t7857
 
5.0%
i5524
 
3.5%
r4074
 
2.6%
Other values (8)18079
11.6%
Uppercase Letter
ValueCountFrequency (%)
V11457
79.3%
N1331
 
9.2%
T1233
 
8.5%
P217
 
1.5%
A217
 
1.5%
Space Separator
ValueCountFrequency (%)
17276
100.0%
Other Punctuation
ValueCountFrequency (%)
'7522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin170803
87.3%
Common24798
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a25380
14.9%
c23131
13.5%
e20117
11.8%
s15945
9.3%
n14929
8.7%
d11674
6.8%
V11457
6.7%
é9638
 
5.6%
t7857
 
4.6%
i5524
 
3.2%
Other values (13)25151
14.7%
Common
ValueCountFrequency (%)
17276
69.7%
'7522
30.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII184632
94.4%
None10969
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a25380
13.7%
c23131
12.5%
e20117
10.9%
17276
9.4%
s15945
8.6%
n14929
8.1%
d11674
 
6.3%
V11457
 
6.2%
t7857
 
4.3%
'7522
 
4.1%
Other values (13)29344
15.9%
None
ValueCountFrequency (%)
é9638
87.9%
ë1331
 
12.1%

ferie
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
False
24777 
True
 
748
ValueCountFrequency (%)
False24777
97.1%
True748
 
2.9%
2022-10-13T09:32:56.979294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Nombre entrees
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct235
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.436905
Minimum0
Maximum288
Zeros2268
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size199.5 KiB
2022-10-13T09:32:57.112534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q323
95-th percentile72
Maximum288
Range288
Interquartile range (IQR)19

Descriptive statistics

Standard deviation28.07272751
Coefficient of variation (CV)1.444300289
Kurtosis20.05675182
Mean19.436905
Median Absolute Deviation (MAD)8
Skewness3.64856868
Sum496127
Variance788.0780299
MonotonicityNot monotonic
2022-10-13T09:32:57.265154image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02268
 
8.9%
21740
 
6.8%
41448
 
5.7%
31188
 
4.7%
51149
 
4.5%
61136
 
4.5%
7966
 
3.8%
8948
 
3.7%
1884
 
3.5%
9828
 
3.2%
Other values (225)12970
50.8%
ValueCountFrequency (%)
02268
8.9%
1884
 
3.5%
21740
6.8%
31188
4.7%
41448
5.7%
51149
4.5%
61136
4.5%
7966
3.8%
8948
3.7%
9828
 
3.2%
ValueCountFrequency (%)
2886
< 0.1%
2875
< 0.1%
2862
 
< 0.1%
2854
< 0.1%
2842
 
< 0.1%
2831
 
< 0.1%
2812
 
< 0.1%
2781
 
< 0.1%
2771
 
< 0.1%
2741
 
< 0.1%

Interactions

2022-10-13T09:32:42.123740image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:30.666130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.033218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.341269image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.603356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.017375image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.231418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.452499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.742521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.269745image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:31.041145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.184230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.483281image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.741326image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.143411image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.365427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.593517image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.877529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.423753image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:31.347158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.340230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.634280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.886328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.285436image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.511431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.735479image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.022529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.571758image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:31.699172image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.484262image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.777296image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.032334image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.426424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.653454image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.882521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.159703image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.714761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:31.923180image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.620246image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.918311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.174340image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.558395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.792441image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.023526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.448752image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.858769image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:32.138189image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.766258image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.048331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.314346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.688433image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.917453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.160527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.576749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:42.995776image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:32.451200image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:33.905250image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.181310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.451351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.821408image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.043452image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.302503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.709728image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:43.140785image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:32.751207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.041266image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.324307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.589358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:37.957413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.182497image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.464507image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.848729image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:43.271470image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:32.891214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:34.192263image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:35.461349image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:36.723395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:38.091415image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:39.311462image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:40.599515image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-13T09:32:41.979741image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-10-13T09:32:57.417704image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-10-13T09:32:57.727387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-10-13T09:32:57.991252image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-10-13T09:32:58.238722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-10-13T09:32:58.624267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-10-13T09:32:43.665685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-10-13T09:32:45.237998image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-10-13T09:32:46.700752image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-10-13T09:32:47.698160image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

date_timeSalleFilmVersionReliefPayantsGratuitsPlaces libresTaux remplissageFullTitleAdultReleaseLanguageGenrePopularityVote_averageVote_countOverviewTempérature maximaleTempérature minimaleVitesse du ventTempérature du ventPrécipitationsHumiditéVisibilitéCouverture nuageuseIndice de chaleurPoint de roséePressionHeure du lever du soleilHeure du coucher du soleilDurée du jourL'avis de historique-meteo.netvacances_zone_avacances_zone_bvacances_zone_cnom_vacancesferieNombre entrees
02018-11-27 09:45:00SALLE 6L'île De Black MórFR2D136.010.0142.050.69L'île de Black MórFalse2004-02-11fr['Animation', 'Adventure', 'Family']1.1826.114.0En 1803, sur les côtes des Cornouailles, Le Kid, un gamin de quinze ans, s'échappe de l'orphelinat où il vivait comme un bagnard. Il ignore son vrai nom et a pour seule richesse la carte d'une île au trésor tombée du livre de Black Mór, un célèbre pirate auquel il souhaiterait ressembler. Avec deux pillards d'épaves, Mac Gregor et La Ficelle, Le Kid s'empare du bateau des garde-côtes et se lance à la recherche de la fameuse île à l'autre bout de l'Océan Atlantique. Mais rien ne se passe comme dans les livres de pirates... En quête de son identité, Le Kid est plus fragile qu'on ne le croit, et bien des aventures l'attendent avant d'arriver à l'Ile de Black Mór...19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse146.0
12018-11-27 10:55:00SALLE 2Diamant NoirFR2D53.0NaN91.036.81Diamant noirFalse2016-06-08fr['Thriller', 'Crime']2.9305.843.0Pier Ulmann vivote à Paris, entre chantiers et larcins qu’il commet pour le compte de Rachid, sa seule « famille ». Son histoire le rattrape le jour où son père est retrouvé mort dans la rue, après une longue déchéance. Bête noire d’une riche famille de diamantaires basée à Anvers, il ne lui laisse rien, à part l'histoire de son bannissement par les Ulmann et une soif amère de vengeance. Sur l’invitation de son cousin Gabi, Pier se rend à Anvers pour rénover les bureaux de la prestigieuse firme Ulmann. La consigne de Rachid est simple : « Tu vas là-bas pour voir, et pour prendre. » Mais un diamant a beaucoup de facettes…19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse53.0
22018-11-27 14:00:00SALLE 2Sobibor, 14 Octobre 1943, 16 HeuresFR2D54.0NaN90.037.50Sobibor, 14 Octobre 1943, 16 HeuresFalse2001-05-13fr['Documentary']1.4006.18.0Sobibor, 14 octobre 1943, 16 heures : lieu, heure, jour, mois et année de la seule révolte réussie d'un camp d'extermination nazie en Pologne. 365 prisonniers parvinrent à s'évader, mais seuls 47 d'entre eux survécurent aux atrocités de la guerre. Claude Lanzmann a rencontré Yehuda Lerner pendant le tournage de Shoah, à Jérusalem en 1979. Dans ce documentaire, ce dernier s'est confié au réalisateur.19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse54.0
32018-11-27 20:30:00SALLE 1Cold WarVO2D6.0NaN87.06.45Cold WarFalse2017-11-19en['Comedy', 'Romance']2.6287.310.0Lorsqu'un jeune couple attrape la redoutable grippe du raton laveur après après avoir emménagé ensemble, ce petit rhume inoffensif se transforme rapidement en guerre totale.19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse6.0
42018-11-27 20:30:00SALLE 2Bohemian RhapsodyVF2D64.0NaN80.044.44Bohemian RhapsodyFalse2018-10-24en['Music', 'Drama', 'History']67.3838.015080.0Le parcours de Queen et son leader Freddie Mercury, de la formation du groupe à son apparition au concert Live Aid en 1985.19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse64.0
52018-11-27 20:30:00SALLE 3Les Animaux Fantastiques : Les Crimes De GriVF2D25.0NaN167.013.02Fantastic Beasts: The Crimes of GrindelwaldFalse2018-11-14en['Fantasy', 'Adventure', 'Action']51.6416.99581.01927 : Quelques mois après sa capture, le célèbre sorcier Gellert Grindelwald s'évade comme il l'avait promis et de façon spectaculaire. Réunissant de plus en plus de partisans, il est à l'origine d'attaque d'humains normaux par des sorciers et seul celui qu'il considérait autrefois comme un ami, Albus Dumbledore, semble capable de l'arrêter. Mais Dumbledore va devoir faire appel au seul sorcier ayant déjoué les plans de Grindelwald auparavant : son ancien élève Norbert Dragonneau. L'aventure qui les attend réunit Norbert avec Tina, Queenie et Jacob, mais cette mission va également tester la loyauté de chacun face aux nouveaux dangers qui se dressent sur leur chemin, dans un monde magique plus dangereux et divisé que jamais.19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse25.0
62018-11-27 20:30:00SALLE 4Casse-noisette Et Les Quatre RoyaumesVF2D38.0NaN55.040.86The Nutcracker and the Four RealmsFalse2018-10-26en['Fantasy', 'Adventure', 'Family']33.5406.11883.0La jeune Clara se retrouve plongée dans un univers parallèle abritant les royaumes des Flocons de neige, des Fleurs, des Délices, mais aussi celui de Mère Gigogne, un véritable tyran qu’elle va devoir affronter afin de récupérer une précieuse clé dérobée par une bande de souris…19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse38.0
72018-11-27 20:30:00SALLE 5Lola Et Ses FrèresFR2D32.0NaN82.028.07Lola et ses frèresFalse2018-11-28fr['Comedy']4.5686.5103.0Lola a deux frères : Benoît, qui se marie pour la troisième fois, et Pierre, qui débarque en retard au mariage… Excuses, reproches, engueulades, brouilles, chacun essaie de vivre sa vie de son côté. Benoît va devenir père sans y être prêt. Lola fait la rencontre de Zoher alors qu’elle s'occupe de son divorce. Quant à Pierre, ses problèmes professionnels s'enveniment. Tout dans leur vie devrait les éloigner, mais ces trois-là sont inséparables…19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse32.0
82018-11-27 20:30:00SALLE 6Astérix - Le Secret De La Potion MagiqueFR2D60.0NaN228.020.83Astérix - Le Secret de la Potion MagiqueFalse2018-05-12fr['Family', 'Animation', 'Comedy', 'Adventure']16.4236.91005.0À la suite d’une chute lors de la cueillette du gui, le druide Panoramix décide qu’il est temps d’assurer l’avenir du village. Accompagné d’Astérix et Obélix, il entreprend de parcourir le monde gaulois à la recherche d’un jeune druide talentueux à qui transmettre le Secret de la Potion Magique…19km/h-2°5mm91%9.375km73%6.02°C1023hPa07:57:0017:02:009:5:0très défavorableFalseFalseFalseNaNFalse60.0
92018-11-28 14:00:00SALLE 1Les ChatouillesFR2D3.0NaN90.03.23Les ChatouillesFalse2018-11-14fr['Drama']9.2947.5268.0Odette, jolie trentenaire, est une danseuse drôle, extrême, et totalement rock’n roll. Grâce à ses séances chez le psy, elle va se remémorer sa jeunesse chaotique, dramatique, cocasse. En revivant des séquences de sa vie, elle sera confrontée au déni, à l’indifférence et surtout à sa propre question : sera-t-elle capable de surmonter sa douleur et de vivre enfin ?11°5km/h0mm90%10km42%11.05°C1024hPa07:58:0017:02:009:4:0très défavorableFalseFalseFalseNaNFalse3.0

Last rows

date_timeSalleFilmVersionReliefPayantsGratuitsPlaces libresTaux remplissageFullTitleAdultReleaseLanguageGenrePopularityVote_averageVote_countOverviewTempérature maximaleTempérature minimaleVitesse du ventTempérature du ventPrécipitationsHumiditéVisibilitéCouverture nuageuseIndice de chaleurPoint de roséePressionHeure du lever du soleilHeure du coucher du soleilDurée du jourL'avis de historique-meteo.netvacances_zone_avacances_zone_bvacances_zone_cnom_vacancesferieNombre entrees
255152022-08-07 18:20:00SALLE 3Top Gun: MaverickVF2DNaNNaN192.0NaNTop Gun: MaverickFalse2022-05-24en['Action', 'Drama']1554.9198.44216.0Après avoir été l’un des meilleurs pilotes de chasse de l'Aéronavale américaine pendant plus de trente ans, Pete “Maverick" Mitchell continue à repousser ses limites en tant que pilote d'essai. Il refuse de monter en grade, car cela l’obligerait à renoncer à voler. Il est chargé de former un détachement de jeunes diplômés de l’école Top Gun pour une mission spéciale qu’aucun pilote n'aurait jamais imaginée. Lors de cette mission, Maverick rencontre le lieutenant Bradley “Rooster” Bradshaw, le fils de son défunt ami, le navigateur Nick “Goose” Bradshaw. Face à un avenir incertain, hanté par ses fantômes, Maverick va devoir affronter ses pires cauchemars au cours d’une mission qui exigera les plus grands sacrifices.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255162022-08-07 18:20:00SALLE 6Thor: Love And ThunderVF2DNaNNaN288.0NaNThor: Love and ThunderFalse2022-07-06en['Fantasy', 'Action', 'Comedy']1905.4086.84117.0Alors que Thor est en pleine introspection et en quête de sérénité, sa retraite est interrompue par un tueur galactique connu sous le nom de Gorr, qui s’est donné pour mission d’exterminer tous les dieux. Pour affronter cette menace, Thor demande l’aide de Valkyrie, de Korg et de son ex-petite amie Jane Foster, qui, à sa grande surprise, manie inexplicablement son puissant marteau, le Mjolnir. Ensemble, ils se lancent dans une dangereuse aventure cosmique pour comprendre les motivations qui poussent Gorr à la vengeance et l’arrêter avant qu’il ne soit trop tard.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255172022-08-07 18:30:00SALLE 2Joyeuse Retraite 2FR2DNaNNaN144.0NaNJoyeuse retraite 2False2022-07-20fr['Comedy']3.4343.89.0lls pensaient enfin passer une retraite tranquille… 3 ans ont passé. Marilou et Philippe décident de faire découvrir à leurs petits-enfants leur nouvelle maison de vacances au Portugal. Mais une fois sur place, ils découvrent horrifiés que la maison est encore en chantier ! Ce n’est que le début des galères pour les grands-parents car bientôt… ils perdent les gamins. Il ne leur reste plus que deux jours pour les retrouver, avant que leurs parents ne les rejoignent.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255182022-08-07 18:30:00SALLE 4L'année Du RequinFR2DNaNNaN93.0NaNL'Année du requinFalse2022-08-03fr['Action']1.4655.720.0Maja, gendarme maritime dans les landes, voit se réaliser son pire cauchemar : prendre sa retraite anticipée ! Thierry, son mari, a déjà prévu la place de camping et le mobil home. Mais la disparition d’un vacancier met toute la côte en alerte : un requin rôde dans la baie ! Aidée de ses jeunes collègues Eugénie et Blaise, elle saute sur l’occasion pour s’offrir une dernière mission.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255192022-08-07 20:30:00SALLE 1As BestasVO2DNaNNaN93.0NaNAs bestasFalse2022-07-20es['Thriller']5.6897.686.0Antoine et Olga, un couple de français, sont installés depuis longtemps dans un petit village de Galice. Ils pratiquent une agriculture écoresponsable et restaurent des maisons abandonnées pour faciliter le repeuplement. Tout devrait être idyllique sans leur opposition à un projet d’éolienne qui crée un grave conflit avec leurs voisins. La tension va monter jusqu’à l’irréparable.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255202022-08-07 20:30:00SALLE 2Bullet TrainVF2DNaNNaN144.0NaNBullet TrainFalse2022-07-03en['Action', 'Comedy', 'Thriller']4442.4437.51627.0Coccinelle est un assassin malchanceux et particulièrement déterminé à accomplir sa nouvelle mission paisiblement après que trop d'entre elles aient déraillé. Mais le destin en a décidé autrement et l'embarque dans le train le plus rapide au monde aux côtés d'adversaires redoutables qui ont tous un point commun, mais dont les intérêts divergent radicalement... Il doit alors tenter par tous les moyens de descendre du train.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255212022-08-07 20:30:00SALLE 4Thor: Love And ThunderVF2DNaNNaN93.0NaNThor: Love and ThunderFalse2022-07-06en['Fantasy', 'Action', 'Comedy']1905.4086.84117.0Alors que Thor est en pleine introspection et en quête de sérénité, sa retraite est interrompue par un tueur galactique connu sous le nom de Gorr, qui s’est donné pour mission d’exterminer tous les dieux. Pour affronter cette menace, Thor demande l’aide de Valkyrie, de Korg et de son ex-petite amie Jane Foster, qui, à sa grande surprise, manie inexplicablement son puissant marteau, le Mjolnir. Ensemble, ils se lancent dans une dangereuse aventure cosmique pour comprendre les motivations qui poussent Gorr à la vengeance et l’arrêter avant qu’il ne soit trop tard.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255222022-08-07 20:30:00SALLE 5L'année Du RequinFR2DNaNNaN114.0NaNL'Année du requinFalse2022-08-03fr['Action']1.4655.720.0Maja, gendarme maritime dans les landes, voit se réaliser son pire cauchemar : prendre sa retraite anticipée ! Thierry, son mari, a déjà prévu la place de camping et le mobil home. Mais la disparition d’un vacancier met toute la côte en alerte : un requin rôde dans la baie ! Aidée de ses jeunes collègues Eugénie et Blaise, elle saute sur l’occasion pour s’offrir une dernière mission.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255232022-08-07 20:40:00SALLE 6Les Minions 2 : Il était Une Fois GruVF2DNaNNaN288.0NaNMinions: The Rise of GruFalse2022-06-29en['Animation', 'Family']1450.1727.62137.0Alors que les années 70 battent leur plein, Gru qui grandit en banlieue au milieu des jeans à pattes d’éléphants et des chevelures en fleur, met sur pied un plan machiavélique à souhait pour réussir à intégrer un groupe célèbre de super méchants, connu sous le nom de Vicious 6, dont il est le plus grand fan. Il est secondé dans sa tâche par les Minions, ses petits compagnons aussi turbulents que fidèles. Avec l’aide de Kevin, Stuart, Bob et Otto – un nouveau Minion arborant un magnifique appareil dentaire et un besoin désespéré de plaire - ils vont déployer ensemble des trésors d’ingéniosité afin de construire leur premier repaire, expérimenter leurs premières armes, et lancer leur première mission. Gru passe l’audition pour intégrer l’équipe. Le moins qu’on puisse dire c’est que l’entrevue tourne mal, et soudain court quand Gru leur démontre sa supériorité et se retrouve soudain leur ennemi juré. Regardez ici : https://classic-blog.udn.com/mobile/aaef2970/17722697433°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0
255242022-08-07 20:50:00SALLE 3MenteurFR2DNaNNaN192.0NaNMenteurFalse2022-07-13fr['Comedy']4.3654.939.0Jérôme est un menteur compulsif. Sa famille et ses amis ne supportent plus ses mensonges quotidiens. Ils font tout pour qu’il change d’attitude. N’écoutant pas ce qu’on lui reproche, Jérôme s’enfonce de plus en plus dans le mensonge jusqu’au jour où une malédiction divine le frappe : tous ses mensonges prennent vie. Commence alors pour un lui un véritable cauchemar.33°10°15km/hNaN62%10km3%32.011°C1019hPa06:33:0021:02:0014:29:0favorableTrueTrueTrueVacances d'étéFalse0.0